EDAM http://edamontology.org/ "EDAM relations and concept properties"
EDAM_data http://edamontology.org/data_ "EDAM types of data"
EDAM_format http://edamontology.org/format_ "EDAM data formats"
EDAM_operation http://edamontology.org/operation_ "EDAM operations"
EDAM_topic http://edamontology.org/topic_ "EDAM topics"
EDAM editors: Jon Ison, Matúš Kalaš, Hervé Ménager, and Veit Schwämmle. Contributors: see http://edamontologydocs.readthedocs.io/en/latest/contributors.html. License: see http://edamontologydocs.readthedocs.io/en/latest/license.html.
EDAM is an ontology of well established, familiar concepts that are prevalent within bioinformatics, including types of data and data identifiers, data formats, operations and topics. EDAM is a simple ontology - essentially a set of terms with synonyms and definitions - organised into an intuitive hierarchy for convenient use by curators, software developers and end-users. EDAM is suitable for large-scale semantic annotations and categorisation of diverse bioinformatics resources. EDAM is also suitable for diverse application including for example within workbenches and workflow-management systems, software distributions, and resource registries.
Bioinformatics operations, data types, formats, identifiers and topics
concept_properties "EDAM concept properties"
'Citation' concept property ('citation' metadata tag) contains a dereferenceable URI, preferrably including a DOI, pointing to a citeable publication of the given data format.
A comment explaining why the comment should be or was deprecated, including name of person commenting (jison, mkalas etc.)
'Documentation' trailing modifier (qualifier, 'documentation') of 'xref' links of 'Format' concepts. When 'true', the link is pointing to a page with explanation, description, documentation, or specification of the given data format.
'Example' concept property ('example' metadata tag) lists examples of valid values of types of identifiers (accessions). Applicable to some other types of data, too.
Separated by bar ('|'). For more complex data and data formats, it can be a link to a website with examples, instead.
'File extension' concept property ('file_extension' metadata tag) lists examples of usual file extensions of formats.
N.B.: File extensions that are not correspondigly defined at http://filext.com are recorded in EDAM only if not in conflict with http://filext.com, and/or unique and usual within life-science computing.
Separated by bar ('|'), without a dot ('.') prefix, preferrably not all capital characters.
"Supported by the given data format" here means, that the given format enables representation of data that satisfies the information standard.
'Information standard' trailing modifier (qualifier, 'information_standard') of 'xref' links of 'Format' concepts. When 'true', the link is pointing to an information standard supported by the given data format.
When 'true', the concept has been proposed to be deprecated.
When 'true', the concept has been proposed to be refactored.
When 'true', the concept has been proposed or is supported within Debian as a tag.
'Media type' trailing modifier (qualifier, 'media_type') of 'xref' links of 'Format' concepts. When 'true', the link is pointing to a page specifying a media type of the given data format.
Whether terms associated with this concept are recommended for use in annotation.
Version in which a concept was made obsolete.
EDAM concept URI of the erstwhile "parent" of a now deprecated concept.
EDAM concept URI of an erstwhile related concept (by has_input, has_output, has_topic, is_format_of, etc.) of a now deprecated concept.
'Ontology used' concept property ('ontology_used' metadata tag) of format concepts links to a domain ontology that is used inside the given data format, or contains a note about ontology use within the format.
'Organisation' trailing modifier (qualifier, 'organisation') of 'xref' links of 'Format' concepts. When 'true', the link is pointing to an organisation that developed, standardised, and maintains the given data format.
A comment explaining the proposed refactoring, including name of person commenting (jison, mkalas etc.)
'Regular expression' concept property ('regex' metadata tag) specifies the allowed values of types of identifiers (accessions). Applicable to some other types of data, too.
'Repository' trailing modifier (qualifier, 'repository') of 'xref' links of 'Format' concepts. When 'true', the link is pointing to the public source-code repository where the given data format is developed or maintained.
Name of thematic editor (http://biotools.readthedocs.io/en/latest/governance.html#registry-editors) responsible for this concept and its children.
'A has_format B' defines for the subject A, that it has the object B as its data format.
Subject A can be any concept or entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that is (or is in a role of) 'Data', or an input, output, input or output argument of an 'Operation'. Object B can either be a concept that is a 'Format', or in unexpected cases an entity outside of an ontology that is a 'Format' or is in the role of a 'Format'. In EDAM, 'has_format' is not explicitly defined between EDAM concepts, only the inverse 'is_format_of'.
'A has_function B' defines for the subject A, that it has the object B as its function.
Subject A can be any concept or entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated). Object B can either be a concept that is (or is in a role of) a function, or an entity outside of an ontology that is (or is in a role of) a function specification. In the scope of EDAM, 'has_function' serves only for relating annotated entities outside of EDAM with 'Operation' concepts.
Is defined anywhere? Not in the 'unknown' version of RO. 'OBO_REL:bearer_of' is narrower in the sense that it only relates ontological categories (concepts) that are an 'independent_continuant' (snap:IndependentContinuant) with ontological categories that are a 'specifically_dependent_continuant' (snap:SpecificallyDependentContinuant), and broader in the sense that it relates with any borne objects not just functions of the subject.
'A has_identifier B' defines for the subject A, that it has the object B as its identifier.
Subject A can be any concept or entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated). Object B can either be a concept that is an 'Identifier', or an entity outside of an ontology that is an 'Identifier' or is in the role of an 'Identifier'. In EDAM, 'has_identifier' is not explicitly defined between EDAM concepts, only the inverse 'is_identifier_of'.
'A has_input B' defines for the subject A, that it has the object B as a necessary or actual input or input argument.
Subject A can either be concept that is or has an 'Operation' function, or an entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that has an 'Operation' function or is an 'Operation'. Object B can be any concept or entity. In EDAM, only 'has_input' is explicitly defined between EDAM concepts ('Operation' 'has_input' 'Data'). The inverse, 'is_input_of', is not explicitly defined.
'OBO_REL:has_participant' is narrower in the sense that it only relates ontological categories (concepts) that are a 'process' (span:Process) with ontological categories that are a 'continuant' (snap:Continuant), and broader in the sense that it relates with any participating objects not just inputs or input arguments of the subject.
'A has_output B' defines for the subject A, that it has the object B as a necessary or actual output or output argument.
Subject A can either be concept that is or has an 'Operation' function, or an entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that has an 'Operation' function or is an 'Operation'. Object B can be any concept or entity. In EDAM, only 'has_output' is explicitly defined between EDAM concepts ('Operation' 'has_output' 'Data'). The inverse, 'is_output_of', is not explicitly defined.
'OBO_REL:has_participant' is narrower in the sense that it only relates ontological categories (concepts) that are a 'process' (span:Process) with ontological categories that are a 'continuant' (snap:Continuant), and broader in the sense that it relates with any participating objects not just outputs or output arguments of the subject. It is also not clear whether an output (result) actually participates in the process that generates it.
'A has_topic B' defines for the subject A, that it has the object B as its topic (A is in the scope of a topic B).
Subject A can be any concept or entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated). Object B can either be a concept that is a 'Topic', or in unexpected cases an entity outside of an ontology that is a 'Topic' or is in the role of a 'Topic'. In EDAM, only 'has_topic' is explicitly defined between EDAM concepts ('Operation' or 'Data' 'has_topic' 'Topic'). The inverse, 'is_topic_of', is not explicitly defined.
'A is_format_of B' defines for the subject A, that it is a data format of the object B.
Subject A can either be a concept that is a 'Format', or in unexpected cases an entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that is a 'Format' or is in the role of a 'Format'. Object B can be any concept or entity outside of an ontology that is (or is in a role of) 'Data', or an input, output, input or output argument of an 'Operation'. In EDAM, only 'is_format_of' is explicitly defined between EDAM concepts ('Format' 'is_format_of' 'Data'). The inverse, 'has_format', is not explicitly defined.
Is defined anywhere? Not in the 'unknown' version of RO. 'OBO_REL:quality_of' might be seen narrower in the sense that it only relates subjects that are a 'quality' (snap:Quality) with objects that are an 'independent_continuant' (snap:IndependentContinuant), and is broader in the sense that it relates any qualities of the object.
'A is_function_of B' defines for the subject A, that it is a function of the object B.
Subject A can either be concept that is (or is in a role of) a function, or an entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that is (or is in a role of) a function specification. Object B can be any concept or entity. Within EDAM itself, 'is_function_of' is not used.
Is defined anywhere? Not in the 'unknown' version of RO. 'OBO_REL:function_of' only relates subjects that are a 'function' (snap:Function) with objects that are an 'independent_continuant' (snap:IndependentContinuant), so for example no processes. It does not define explicitly that the subject is a function of the object.
Is defined anywhere? Not in the 'unknown' version of RO. 'OBO_REL:inheres_in' is narrower in the sense that it only relates ontological categories (concepts) that are a 'specifically_dependent_continuant' (snap:SpecificallyDependentContinuant) with ontological categories that are an 'independent_continuant' (snap:IndependentContinuant), and broader in the sense that it relates any borne subjects not just functions.
'A is_identifier_of B' defines for the subject A, that it is an identifier of the object B.
Subject A can either be a concept that is an 'Identifier', or an entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that is an 'Identifier' or is in the role of an 'Identifier'. Object B can be any concept or entity outside of an ontology. In EDAM, only 'is_identifier_of' is explicitly defined between EDAM concepts (only 'Identifier' 'is_identifier_of' 'Data'). The inverse, 'has_identifier', is not explicitly defined.
'A is_input_of B' defines for the subject A, that it as a necessary or actual input or input argument of the object B.
Subject A can be any concept or entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated). Object B can either be a concept that is or has an 'Operation' function, or an entity outside of an ontology that has an 'Operation' function or is an 'Operation'. In EDAM, 'is_input_of' is not explicitly defined between EDAM concepts, only the inverse 'has_input'.
'OBO_REL:participates_in' is narrower in the sense that it only relates ontological categories (concepts) that are a 'continuant' (snap:Continuant) with ontological categories that are a 'process' (span:Process), and broader in the sense that it relates any participating subjects not just inputs or input arguments.
'A is_output_of B' defines for the subject A, that it as a necessary or actual output or output argument of the object B.
Subject A can be any concept or entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated). Object B can either be a concept that is or has an 'Operation' function, or an entity outside of an ontology that has an 'Operation' function or is an 'Operation'. In EDAM, 'is_output_of' is not explicitly defined between EDAM concepts, only the inverse 'has_output'.
'OBO_REL:participates_in' is narrower in the sense that it only relates ontological categories (concepts) that are a 'continuant' (snap:Continuant) with ontological categories that are a 'process' (span:Process), and broader in the sense that it relates any participating subjects not just outputs or output arguments. It is also not clear whether an output (result) actually participates in the process that generates it.
'A is_topic_of B' defines for the subject A, that it is a topic of the object B (a topic A is the scope of B).
Subject A can either be a concept that is a 'Topic', or in unexpected cases an entity outside of an ontology (or an ontology concept in a role of an entity being semantically annotated) that is a 'Topic' or is in the role of a 'Topic'. Object B can be any concept or entity outside of an ontology. In EDAM, 'is_topic_of' is not explicitly defined between EDAM concepts, only the inverse 'has_topic'.
A type of computational resource used in bioinformatics.
Information, represented in an information artefact (data record) that is 'understandable' by dedicated computational tools that can use the data as input or produce it as output.
EDAM does not distinguish a data record (a tool-understandable information artefact) from data or datum (its content, the tool-understandable encoding of an information).
EDAM does not distinguish the multiplicity of data, such as one data item (datum) versus a collection of data (data set).
A bioinformatics package or tool, e.g. a standalone application or web service.
A digital data archive typically based around a relational model but sometimes using an object-oriented, tree or graph-based model.
An ontology of biological or bioinformatics concepts and relations, a controlled vocabulary, structured glossary etc.
A directory on disk from which files are read.
Controlled vocabulary from National Library of Medicine. The MeSH thesaurus is used to index articles in biomedical journals for the Medline/PubMED databases.
Controlled vocabulary for gene names (symbols) from HUGO Gene Nomenclature Committee.
Compendium of controlled vocabularies for the biomedical domain (Unified Medical Language System).
A text token, number or something else which identifies an entity, but which may not be persistent (stable) or unique (the same identifier may identify multiple things).
Almost exact but limited to identifying resources.
An entry (retrievable via URL) from a biological database.
A specification of a chemical structure.
A QSAR quantitative descriptor (name-value pair) of chemical structure.
QSAR descriptors have numeric values that quantify chemical information encoded in a symbolic representation of a molecule. They are used in quantitative structure activity relationship (QSAR) applications. Many subtypes of individual descriptors (not included in EDAM) cover various types of protein properties.
Deprecated because this is bloat / confusing & better handled as an EDAM Format concept - "raw" sequences just imply a particular format (i.e. one with a vanilla string, possible in a particular alphabet, with no metadata).
A raw molecular sequence (string of characters) which might include ambiguity, unknown positions and non-sequence characters.
Non-sequence characters may be used for example for gaps and translation stop.
A molecular sequence and associated metadata.
A collection of one or typically multiple molecular sequences (which can include derived data or metadata) that do not (typically) correspond to molecular sequence database records or entries and which (typically) are derived from some analytical method.
An example is an alignment reference; one or a set of reference molecular sequences, structures, or profiles used for alignment of genomic, transcriptomic, or proteomic experimental data.
This concept may be used for arbitrary sequence sets and associated data arising from processing.
A character used to replace (mask) other characters in a molecular sequence.
A label (text token) describing the type of sequence masking to perform.
Sequence masking is where specific characters or positions in a molecular sequence are masked (replaced) with an another (mask character). The mask type indicates what is masked, for example regions that are not of interest or which are information-poor including acidic protein regions, basic protein regions, proline-rich regions, low compositional complexity regions, short-periodicity internal repeats, simple repeats and low complexity regions. Masked sequences are used in database search to eliminate statistically significant but biologically uninteresting hits.
The strand of a DNA sequence (forward or reverse).
The forward or 'top' strand might specify a sequence is to be used as given, the reverse or 'bottom' strand specifying the reverse complement of the sequence is to be used.
Basic or general information concerning molecular sequences.
This is used for such things as a report including the sequence identifier, type and length.
How the annotation of a sequence feature (for example in EMBL or Swiss-Prot) was derived.
This might be the name and version of a software tool, the name of a database, or 'curated' to indicate a manual annotation (made by a human).
A report of sequence hits and associated data from searching a database of sequences (for example a BLAST search). This will typically include a list of scores (often with statistical evaluation) and a set of alignments for the hits.
The score list includes the alignment score, percentage of the query sequence matched, length of the database sequence entry in this alignment, identifier of the database sequence entry, excerpt of the database sequence entry description etc.
Report on the location of matches ("hits") between sequences, sequence profiles, motifs (conserved or functional patterns) and other types of sequence signatures.
Protein secondary database search results
Search results (protein secondary database)
A "profile-profile alignment" is an alignment of two sequence profiles, each profile typically representing a sequence alignment.
A "sequence-profile alignment" is an alignment of one or more molecular sequence(s) to one or more sequence profile(s) (each profile typically representing a sequence alignment).
This includes reports of hits from a search of a protein secondary or domain database. Data associated with the search or alignment might also be included, e.g. ranked list of best-scoring sequences, a graphical representation of scores etc.
Data files used by motif or profile methods.
Data concering concerning specific or conserved pattern in molecular sequences and the classifiers used for their identification, including sequence motifs, profiles or other diagnostic element.
This can include metadata about a motif or sequence profile such as its name, length, technical details about the profile construction, and so on.
Alignment of exact matches between subsequences (words) within two or more molecular sequences.
A dotplot of sequence similarities identified from word-matching or character comparison.
Alignment of multiple molecular sequences.
Some simple value controlling a sequence alignment (or similar 'match') operation.
A value representing molecular sequence similarity.
Report of general information on a sequence alignment, typically include a description, sequence identifiers and alignment score.
An informative report of molecular sequence alignment-derived data or metadata.
Use this for any computer-generated reports on sequence alignments, and for general information (metadata) on a sequence alignment, such as a description, sequence identifiers and alignment score.
"Sequence-profile alignment" and "Profile-profile alignment" are synonymous with "Sequence signature matches" which was already stated as including matches (alignment) and other data.
A profile-profile alignment (each profile typically representing a sequence alignment).
Alignment of one or more molecular sequence(s) to one or more sequence profile(s) (each profile typically representing a sequence alignment).
A matrix of estimated evolutionary distance between molecular sequences, such as is suitable for phylogenetic tree calculation.
Methods might perform character compatibility analysis or identify patterns of similarity in an alignment or data matrix.
Basic character data from which a phylogenetic tree may be generated.
As defined, this concept would also include molecular sequences, microsatellites, polymorphisms (RAPDs, RFLPs, or AFLPs), restriction sites and fragments
The raw data (not just an image) from which a phylogenetic tree is directly generated or plotted, such as topology, lengths (in time or in expected amounts of variance) and a confidence interval for each length.
A phylogenetic tree is usually constructed from a set of sequences from which an alignment (or data matrix) is calculated. See also 'Phylogenetic tree image'.
Matrix of integer or floating point numbers for amino acid or nucleotide sequence comparison.
The comparison matrix might include matrix name, optional comment, height and width (or size) of matrix, an index row/column (of characters) and data rows/columns (of integers or floats).
Predicted or actual protein topology represented as a string of protein secondary structure elements.
The location and size of the secondary structure elements and intervening loop regions is usually indicated.
Secondary structure (predicted or real) of a protein.
Protein features report (secondary structure)
Super-secondary structure of protein sequence(s).
Super-secondary structures include leucine zippers, coiled coils, Helix-Turn-Helix etc.
Protein features report (super-secondary)
Alignment of the (1D representations of) secondary structure of two or more proteins.
An informative report on protein secondary structure alignment-derived data or metadata.
Secondary structure alignment metadata (protein)
An informative report of secondary structure (predicted or real) of an RNA molecule.
This includes thermodynamically stable or evolutionarily conserved structures such as knots, pseudoknots etc.
Alignment of the (1D representations of) secondary structure of two or more RNA molecules.
An informative report of RNA secondary structure alignment-derived data or metadata.
Secondary structure alignment metadata (RNA)
3D coordinate and associated data for a macromolecular tertiary (3D) structure or part of a structure.
The coordinate data may be predicted or real.
An entry from a molecular tertiary (3D) structure database.
Results (hits) from searching a database of tertiary structure.
Alignment (superimposition) of molecular tertiary (3D) structures.
A tertiary structure alignment will include the untransformed coordinates of one macromolecule, followed by the second (or subsequent) structure(s) with all the coordinates transformed (by rotation / translation) to give a superposition.
An informative report of molecular tertiary structure alignment-derived data.
This is a broad data type and is used a placeholder for other, more specific types.
A value representing molecular structure similarity, measured from structure alignment or some other type of structure comparison.
Some type of structural (3D) profile or template (representing a structure or structure alignment).
A 3D profile-3D profile alignment (each profile representing structures or a structure alignment).
An alignment of a sequence to a 3D profile (representing structures or a structure alignment).
Matrix of values used for scoring sequence-structure compatibility.
Protein sequence-structure scoring matrix
An alignment of molecular sequence to structure (from threading sequence(s) through 3D structure or representation of structure(s)).
An informative report about a specific amino acid.
An informative report about a specific peptide.
An informative human-readable report about one or more specific protein molecules or protein structural domains, derived from analysis of primary (sequence or structural) data.
A report of primarily non-positional data describing intrinsic physical, chemical or other properties of a protein molecule or model.
This is a broad data type and is used a placeholder for other, more specific types. Data may be based on analysis of nucleic acid sequence or structural data, for example reports on the surface properties (shape, hydropathy, electrostatic patches etc) of a protein structure, protein flexibility or motion, and protein architecture (spatial arrangement of secondary structure).
Data concerning the classification of the sequences and/or structures of protein structural domain(s).
structural domains or 3D folds in a protein or polypeptide chain.
An informative report on architecture (spatial arrangement of secondary structure) of a protein structure.
A report on an analysis or model of protein folding properties, folding pathways, residues or sites that are key to protein folding, nucleation or stabilisation centers etc.
Data on the effect of (typically point) mutation on protein folding, stability, structure and function.
This is a broad data type and is used a placeholder for other, more specific types. It is primarily intended to help navigation of EDAM and would not typically be used for annotation.
Protein-protein interaction data from for example yeast two-hybrid analysis, protein microarrays, immunoaffinity chromatography followed by mass spectrometry, phage display etc.
Data concerning the interactions (predicted or known) within or between a protein, structural domain or part of a protein. This includes intra- and inter-residue contacts and distances, as well as interactions with other proteins and non-protein entities such as nucleic acid, metal atoms, water, ions etc.
Protein non-covalent interactions report
An informative report on a specific protein family or other classification or group of protein sequences or structures.
The maximum initial velocity or rate of a reaction. It is the limiting velocity as substrate concentrations get very large.
Km is the concentration (usually in Molar units) of substrate that leads to half-maximal velocity of an enzyme-catalysed reaction.
An informative report about a specific nucleotide base.
Nucleic acid structural properties stiffness, curvature, twist/roll data or other conformational parameters or properties.
A report of primarily non-positional data describing intrinsic physical, chemical or other properties of a nucleic acid molecule.
Data derived from analysis of codon usage (typically a codon usage table) of DNA sequences.
A report on predicted or actual gene structure, regions which make an RNA product and features such as promoters, coding regions, splice sites etc.
Nucleic acid features (gene and transcript structure)
This includes any report on a particular locus or gene. This might include the gene name, description, summary and so on. It can include details about the function of a gene, such as its encoded protein or a functional classification of the gene sequence along according to the encoded protein(s).
A report on the classification of nucleic acid / gene sequences according to the functional classification of their gene products.
stable, naturally occuring mutations in a nucleotide sequence including alleles, naturally occurring mutations such as single base nucleotide substitutions, deletions and insertions, RFLPs and other polymorphisms.
A human-readable collection of information about a specific chromosome.
This includes basic information. e.g. chromosome number, length, karyotype features, chromosome sequence etc.
A human-readable collection of information about the set of genes (or allelic forms) present in an individual, organism or cell and associated with a specific physical characteristic, or a report concerning an organisms traits and phenotypes.
PCR experiments, e.g. quantitative real-time PCR.
Fluorescence trace data generated by an automated DNA sequencer, which can be interprted as a molecular sequence (reads), given associated sequencing metadata such as base-call quality scores.
This is the raw data produced by a DNA sequencing machine.
An assembly of fragments of a (typically genomic) DNA sequence.
Typically, an assembly is a collection of contigs (for example ESTs and genomic DNA fragments) that are ordered, aligned and merged. Annotation of the assembled sequence might be included.
Perhaps surprisingly, the definition of 'SO:assembly' is narrower than the 'SO:sequence_assembly'.
Radiation hybrid scores (RH) scores for one or more markers.
Radiation Hybrid (RH) scores are used in Radiation Hybrid mapping.
A human-readable collection of information about the linkage of alleles.
This includes linkage disequilibrium; the non-random association of alleles or polymorphisms at two or more loci (not necessarily on the same chromosome).
Data quantifying the level of expression of (typically) multiple genes, derived for example from microarray experiments.
microarray experiments including conditions, protocol, sample:data relationships etc.
Data on oligonucleotide probes (typically for use with DNA microarrays).
Output from a serial analysis of gene expression (SAGE) experiment.
Massively parallel signature sequencing (MPSS) data.
Tag to gene assignments (tag mapping) of SAGE, MPSS and SBS data. Typically this is the sequencing-based expression profile annotated with gene identifiers.
Sequence tag profile (with gene assignment)
Nuclear magnetic resonance (NMR) raw data, typically for a protein.
Protein secondary structure from protein coordinate or circular dichroism (CD) spectroscopic data.
Protein circular dichroism (CD) spectroscopic data
Volume map data from electron microscopy.
Annotation on a structural 3D model (volume map) from electron microscopy.
Two-dimensional gel electrophoresis image
A set of peptide masses (peptide mass fingerprint) from mass spectrometry.
A molecular weight standard fingerprint is standard protonated molecular masses e.g. from trypsin (modified porcine trypsin, Promega) and keratin peptides.
Protein or peptide identifications with evidence supporting the identifications, for example from comparing a peptide mass fingerprint (from mass spectrometry) to a sequence database, or the set of typical spectra one obtains when running a protein through a mass spectrometer.
An informative report about a specific biological pathway or network, typically including a map (diagram) of the pathway.
A map (typically a diagram) of a biological pathway.
A definition of a data resource serving one or more types of data, including metadata and links to the resource or data proper.
Basic information, annotation or documentation concerning a workflow (but not the workflow itself).
A biological model represented in mathematical terms.
A value representing estimated statistical significance of some observed data; typically sequence database hits.
Resource definition for an EMBOSS database.
Information on a version of software or data, for example name, version number and release date.
Development status / maturity may be part of the version information, for example in case of tools, standards, or some data records.
A mapping of the accession numbers (or other database identifier) of entries between (typically) two biological or biomedical databases.
The cross-mapping is typically a table where each row is an accession number and each column is a database being cross-referenced. The cells give the accession number or identifier of the corresponding entry in a database. If a cell in the table is not filled then no mapping could be found for the database. Additional information might be given on version, date etc.
An index of data of biological relevance.
A human-readable collection of information concerning an analysis of an index of biological data.
Basic information on bioinformatics database(s) or other data sources such as name, type, description, URL etc.
Basic information about one or more bioinformatics applications or packages, such as name, type, description, or other documentation.
Textual metadata on a submitted or completed job.
Textual metadata on a software author or end-user, for example a person or other software.
A human-readable collection of information about a specific chemical compound.
A human-readable collection of information about a particular strain of organism cell line including plants, virus, fungi and bacteria. The data typically includes strain number, organism type, growth conditions, source and so on.
An informative report about a specific scent.
Data concerning or derived from a concept from a biological ontology.
Keyword(s) or phrase(s) used (typically) for text-searching purposes.
Boolean operators (AND, OR and NOT) and wildcard characters may be allowed.
Bibliographic data that uniquely identifies a scientific article, book or other published material.
A bibliographic reference might include information such as authors, title, journal name, date and (possibly) a link to the abstract or full-text of the article if available.
A scientific text, typically a full text article from a scientific journal.
A human-readable collection of information resulting from text mining.
A text mining abstract will typically include an annotated a list of words or sentences extracted from one or more scientific articles.
An identifier of a biological entity or phenomenon.
An identifier that identifies a particular type of data.
This concept exists only to assist EDAM maintenance and navigation in graphical browsers. It does not add semantic information. This branch provides an alternative organisation of the concepts nested under 'Accession' and 'Name'. All concepts under here are already included under 'Accession' or 'Name'.
An identifier of a bioinformatics tool, e.g. an application or web service.
Name or other identifier of a discrete entity (any biological thing with a distinct, discrete physical existence).
Name or other identifier of an entity feature (a physical part or region of a discrete biological entity, or a feature that can be mapped to such a thing).
Name or other identifier of a collection of discrete biological entities.
Name or other identifier of a physical, observable biological occurrence or event.
Identifier (e.g. character symbol) of a specific atom.
A label (text token) describing the type a molecule.
For example, 'Protein', 'DNA', 'RNA' etc.
Unique identifier of a chemical compound.
Unique registry number of a chemical compound.
Code word for a ligand, for example from a PDB file.
Name or other identifier of a nucleotide.
Unique name from Chemical Entities of Biological Interest (ChEBI) of a chemical compound.
This is the recommended chemical name for use for example in database annotation.
IUPAC recommended name of a chemical compound.
International Non-proprietary Name (INN or 'generic name') of a chemical compound, assigned by the World Health Organisation (WHO).
CAS registry number of a chemical compound; a unique numerical identifier of chemicals in the scientific literature, as assigned by the Chemical Abstracts Service.
Beilstein registry number of a chemical compound.
Gmelin registry number of a chemical compound.
3-letter code word for a ligand (HET group) from a PDB file, for example ATP.
String of one or more ASCII characters representing an amino acid.
String of one or more ASCII characters representing a nucleotide.
Identifier of a polypeptide chain from a protein.
This is typically a character (for the chain) appended to a PDB identifier, e.g. 1cukA
Name or other identifier of an enzyme or record from a database of enzymes.
An Enzyme Commission (EC) number of an enzyme.
A specification (partial or complete) of one or more positions or regions of a molecular sequence or map.
A unique identifier of molecular sequence feature, for example an ID of a feature that is unique within the scope of the GFF file.
A position of one or more points (base or residue) in a sequence, or part of such a specification.
Specification of range(s) of sequence positions.
Name or other identifier of an nucleic acid feature.
Name or other identifier of a protein feature.
The type of a sequence feature, typically a term or accession from the Sequence Ontology, for example an EMBL or Swiss-Prot sequence feature key.
A feature key indicates the biological nature of the feature or information about changes to or versions of the sequence.
Typically one of the EMBL or Swiss-Prot feature qualifiers.
Feature qualifiers hold information about a feature beyond that provided by the feature key and location.
A name of a sequence feature, e.g. the name of a feature to be displayed to an end-user. Typically an EMBL or Swiss-Prot feature label.
A feature label identifies a feature of a sequence database entry. When used with the database name and the entry's primary accession number, it is a unique identifier of that feature.
The name of a sequence feature-containing entity adhering to the standard feature naming scheme used by all EMBOSS applications.
String of one or more ASCII characters representing a codon.
An identifier of a gene, such as a name/symbol or a unique identifier of a gene in a database.
The short name of a gene; a single word that does not contain white space characters. It is typically derived from the gene name.
An NCBI RefSeq unique identifier of a gene.
An NCBI UniGene unique identifier of a gene.
Identifier of a gene or feature from the CGD database.
Unique identifier for a gene (or other feature) from the Ensembl database.
Identifier of an entry from the SGD database.
Identifier of a gene from the GeneDB database.
Identifier of an entry from the TIGR database.
Identifier of an gene from the TAIR database.
Identifier of a protein structural domain.
This is typically a character or string concatenated with a PDB identifier and a chain identifier.
Identifier of a protein domain (or other node) from the SCOP database.
Identifier of a protein domain from CATH.
A SCOP concise classification string (sccs) is a compact representation of a SCOP domain classification.
An scss includes the class (alphabetical), fold, superfamily and family (all numerical) to which a given domain belongs.
SCOP concise classification string (sccs)
Unique identifier (number) of an entry in the SCOP hierarchy, for example 33229.
A sunid uniquely identifies an entry in the SCOP hierarchy, including leaves (the SCOP domains) and higher level nodes including entries corresponding to the protein level.
A code number identifying a node from the CATH database.
The name of a biological kingdom (Bacteria, Archaea, or Eukaryotes).
The name of a species (typically a taxonomic group) of organism.
The name of a strain of an organism variant, typically a plant, virus or bacterium.
A string of characters that name or otherwise identify a resource on the Internet.
An identifier of a biological or bioinformatics database.
The name (or part of a name) of a file (of any type).
Name of an ontology of biological or bioinformatics concepts and relations.
A Life Science Identifier (LSID) - a unique identifier of some data.
LSIDs provide a standard way to locate and describe data. An LSID is represented as a Uniform Resource Name (URN) with the following format: URN:LSID:<Authority>:<Namespace>:<ObjectID>[:<Version>]
The name of a biological or bioinformatics database.
The name of a molecular sequence database.
The name of a file (of any type) with restricted possible values.
A file extension is the characters appearing after the final '.' in the file name.
A file base name is the file name stripped of its directory specification and extension.
An identifier of an entry from a database where the same type of identifier is used for objects (data) of different semantic type.
This concept is required for completeness. It should never have child concepts.
An identifier of molecular sequence(s) or entries from a molecular sequence database.
An identifier of a set of molecular sequence(s).
Identifier of a sequence signature (motif or profile) for example from a database of sequence patterns.
Identifier of a molecular sequence alignment, for example a record from an alignment database.
Identifier of a phylogenetic distance matrix.
Identifier of a phylogenetic tree for example from a phylogenetic tree database.
A unique and persistent identifier of a molecular tertiary structure, typically an entry from a structure database.
Identifier or name of a structural (3D) profile or template (representing a structure or structure alignment).
Identifier of an entry from a database of tertiary structure alignments.
Identifier of an index of amino acid physicochemical and biochemical property data.
Identifier of a report of protein interactions from a protein interaction database (typically).
Protein secondary database record identifier
Identifier of a transcription factor (or a TF binding site).
Identifier of an entry from a database of microarray data.
Identifier of an entry from a database of electron microscopy data.
Accession of a report of gene expression (e.g. a gene expression profile) from a database.
Identifier of an entry from a database of genotypes and phenotypes.
Identifier of an entry from a database of biological pathways or networks.
Identifier of a biological or biomedical workflow, typically from a database of workflows.
Identifier of a data type definition from some provider.
Identifier of a mathematical model, typically an entry from a database.
Identifier of an entry from a database of chemicals.
A unique (typically numerical) identifier of a concept in an ontology of biological or bioinformatics concepts and relations.
Unique identifier of a scientific article.
Identifier of an object from the FlyBase database.
Name of an object from the WormBase database, usually a human-readable name.
Class of an object from the WormBase database.
A WormBase class describes the type of object such as 'sequence' or 'protein'.
A persistent, unique identifier of a molecular sequence database entry.
A label (text token) describing a type of molecular sequence.
Sequence type might reflect the molecule (protein, nucleic acid etc) or the sequence itself (gapped, ambiguous etc).
The name of a sequence-based entity adhering to the standard sequence naming scheme used by all EMBOSS applications.
Accession number of a protein sequence database entry.
Accession number of a nucleotide sequence database entry.
Accession number of a RefSeq database entry.
Accession number of a UniProt (protein sequence) database entry. May contain version or isoform number.
An identifier of PIR sequence database entry.
Identifier of a TREMBL sequence database entry.
Primary identifier of a Gramene database entry.
Identifier of a (nucleic acid) entry from the EMBL/GenBank/DDBJ databases.
A unique identifier of an entry (gene cluster) from the NCBI UniGene database.
The EMBOSS type of a molecular sequence.
See the EMBOSS documentation (http://emboss.sourceforge.net/) for a definition of what this includes.
List of EMBOSS Uniform Sequence Addresses (EMBOSS listfile).
An identifier of a cluster of molecular sequence(s).
Unique identifier of an entry from the COG database.
Identifier of a sequence motif, for example an entry from a motif database.
A sequence profile typically represents a sequence alignment.
Identifier of an entry from the ELMdb database of protein functional sites.
Accession number of an entry from the Prosite database.
Unique identifier or name of a HMMER hidden Markov model.
Unique identifier or name of a profile from the JASPAR database.
A label (text token) describing the type of a sequence alignment.
Possible values include for example the EMBOSS alignment types, BLAST alignment types and so on.
A label (text token) describing the type of a phylogenetic tree.
Accession number of an entry from the TreeBASE database.
Accession number of an entry from the TreeFam database.
A label (text token) describing the type of a comparison matrix.
For example 'blosum', 'pam', 'gonnet', 'id' etc. Comparison matrix type may be required where a series of matrices of a certain type are used.
Unique name or identifier of a comparison matrix.
See for example http://www.ebi.ac.uk/Tools/webservices/help/matrix.
An identifier of an entry from the PDB database.
A PDB identification code which consists of 4 characters, the first of which is a digit in the range 0 - 9; the remaining 3 are alpha-numeric, and letters are upper case only. (source: https://cdn.rcsb.org/wwpdb/docs/documentation/file-format/PDB_format_1996.pdf)
Identifier of an entry from the AAindex database.
Accession number of an entry from the BIND database.
Accession number of an entry from the IntAct database.
Name of an InterPro entry, usually indicating the type of protein matches for that entry.
Primary accession number of an InterPro entry.
Every InterPro entry has a unique accession number to provide a persistent citation of database records.
Secondary accession number of an InterPro entry.
Unique identifier of an entry from the Gene3D database.
Unique identifier of an entry from the PIRSF database.
The unique identifier of an entry in the PRINTS database.
Accession number of an entry from the SMART database.
Unique identifier (number) of a hidden Markov model from the Superfamily database.
Accession number of an entry (family) from the TIGRFam database.
A ProDom domain family accession number.
ProDom is a protein domain family database.
Identifier of an entry from the TRANSFAC database.
Accession number of an entry from the ArrayExpress database.
Identifier of an entry from the EMDB electron microscopy database.
Accession number of an entry from the GEO database.
Identifier of an entry from the GermOnline database.
Identifier of an entry from the EMAGE database.
Accession number of an entry from a database of disease.
Identifier of an entry from the HGVbase database.
Identifier of an entry from the HIVDB database.
Identifier of an entry from the OMIM database.
Unique identifier of an object from one of the KEGG databases (excluding the GENES division).
Identifier of an entry from the Reactome database.
Identifier of an entry from the aMAZE database.
Identifier of an pathway from the BioCyc biological pathways database.
Identifier of an entry from the INOH database.
Identifier of an entry from the PATIKA database.
Identifier of an entry from the CPDB (ConsensusPathDB) biological pathways database, which is an identifier from an external database integrated into CPDB.
This concept refers to identifiers used by the databases collated in CPDB; CPDB identifiers are not independently defined.
Identifier of a biological pathway from the Panther Pathways database.
Unique identifier of a MIRIAM data resource.
This is the identifier used internally by MIRIAM for a data type.
The name of a data type from the MIRIAM database.
The URI (URL or URN) of a data entity from the MIRIAM database.
A MIRIAM URI consists of the URI of the MIRIAM data type (PubMed, UniProt etc) followed by the identifier of an element of that data type, for example PMID for a publication or an accession number for a GO term.
The primary name of a data type from the MIRIAM database.
The primary name of a MIRIAM data type is taken from a controlled vocabulary.
A protein entity has the MIRIAM data type 'UniProt', and an enzyme has the MIRIAM data type 'Enzyme Nomenclature'.
A synonymous name of a data type from the MIRIAM database.
A synonymous name for a MIRIAM data type taken from a controlled vocabulary.
Unique identifier of a Taverna workflow.
Name of a biological (mathematical) model.
Unique identifier of an entry from the BioModel database.
Chemical structure specified in PubChem Compound Identification (CID), a non-zero integer identifier for a unique chemical structure.
Identifier of an entry from the ChemSpider database.
Identifier of an entry from the ChEBI database.
An identifier of a concept from the BioPax ontology.
An identifier of a concept from The Gene Ontology.
An identifier of a concept from the MeSH vocabulary.
An identifier of a concept from the HGNC controlled vocabulary.
A stable unique identifier for each taxon (for a species, a family, an order, or any other group in the NCBI taxonomy database.
An identifier of a concept from the Plant Ontology (PO).
An identifier of a concept from the UMLS vocabulary.
An identifier of a concept from Foundational Model of Anatomy.
Classifies anatomical entities according to their shared characteristics (genus) and distinguishing characteristics (differentia). Specifies the part-whole and spatial relationships of the entities, morphological transformation of the entities during prenatal development and the postnatal life cycle and principles, rules and definitions according to which classes and relationships in the other three components of FMA are represented.
An identifier of a concept from the EMAP mouse ontology.
An identifier of a concept from the ChEBI ontology.
An identifier of a concept from the MGED ontology.
An identifier of a concept from the myGrid ontology.
The ontology is provided as two components, the service ontology and the domain ontology. The domain ontology acts provides concepts for core bioinformatics data types and their relations. The service ontology describes the physical and operational features of web services.
Digital Object Identifier (DOI) of a published article.
Medline UI (unique identifier) of an article.
The use of Medline UI has been replaced by the PubMed unique identifier.
The name of a computer package, application, method or function.
The unique name of a signature (sequence classifier) method.
Signature methods from http://www.ebi.ac.uk/Tools/InterProScan/help.html#results include BlastProDom, FPrintScan, HMMPIR, HMMPfam, HMMSmart, HMMTigr, ProfileScan, ScanRegExp, SuperFamily and HAMAP.
This include 'blastn', 'blastp', 'blastx', 'tblastn' and 'tblastx'.
This includes 'fasta3', 'fastx3', 'fasty3', 'fastf3', 'fasts3' and 'ssearch'.
Any collection of multiple protein sequences and associated metadata that do not (typically) correspond to common sequence database records or database entries.
Any collection of multiple nucleotide sequences and associated metadata that do not (typically) correspond to common sequence database records or database entries.
A set of sequences that have been clustered or otherwise classified as belonging to a group including (typically) sequence cluster information.
The cluster might include sequences identifiers, short descriptions, alignment and summary information.
A file of intermediate results from a PSIBLAST search that is used for priming the search in the next PSIBLAST iteration.
A Psiblast checkpoint file uses ASN.1 Binary Format and usually has the extension '.asn'.
Sequences generated by HMMER package in FASTA-style format.
A protein sequence cleaved into peptide fragments (by enzymatic or chemical cleavage) with fragment masses.
Restriction digest fragments from digesting a nucleotide sequence with restriction sites using a restriction endonuclease.
Oligonucleotide primer(s) for PCR and DNA amplification, for example a minimal primer set.
File of sequence vectors used by EMBOSS vectorstrip application, or any file in same format.
vectorstrip cloning vector definition file
A library of nucleotide sequences to avoid during hybridisation events. Hybridisation of the internal oligo to sequences in this library is avoided, rather than priming from them. The file is in a restricted FASTA format.
Primer3 internal oligo mishybridizing library
A nucleotide sequence library of sequences to avoid during amplification (for example repetitive sequences, or possibly the sequences of genes in a gene family that should not be amplified. The file must is in a restricted FASTA format.
File of one or more pairs of primer sequences, as used by EMBOSS primersearch application.
primersearch primer pairs sequence record
The sequences are typically related, for example a family of sequences.
The size (length) of a sequence, subsequence or region in a sequence, or range(s) of lengths.
Word size is used for example in word-based sequence database search methods.
A window is a region of fixed size but not fixed position over a molecular sequence. It is typically moved (computationally) over a sequence during scoring.
Specification of range(s) of length of sequences.
Report on basic information about a molecular sequence such as name, accession number, type (nucleic or protein), length, description etc.
An informative report about non-positional sequence features, typically a report on general molecular sequence properties derived from sequence analysis.
Annotation of positional features of molecular sequence(s), i.e. that can be mapped to position(s) in the sequence.
This includes annotation of positional sequence features, organised into a standard feature table, or any other report of sequence features. General feature reports are a source of sequence feature table information although internal conversion would be required.
Comparative data on sequence features such as statistics, intersections (and data on intersections), differences etc.
A report of general sequence properties derived from protein sequence data.
A report of general sequence properties derived from nucleotide sequence data.
A report on sequence complexity, for example low-complexity or repeat regions in sequences.
A report on ambiguity in molecular sequence(s).
A report (typically a table) on character or word composition / frequency of a molecular sequence(s).
A report on peptide fragments of certain molecular weight(s) in one or more protein sequences.
A plot of third base position variability in a nucleotide sequence.
A table of character or word composition / frequency of a molecular sequence.
A table of base frequencies of a nucleotide sequence.
A table of word composition of a nucleotide sequence.
A table of amino acid frequencies of a protein sequence.
Sequence composition (amino acid frequencies)
A table of amino acid word composition of a protein sequence.
Annotation of a molecular sequence in DAS format.
Annotation of positional sequence features, organised into a standard feature table.
A map of (typically one) DNA sequence annotated with positional or non-positional features.
An informative report on intrinsic positional features of a nucleotide sequence, formatted to be machine-readable.
This includes nucleotide sequence feature annotation in any known sequence feature table format and any other report of nucleic acid features.
An informative report on intrinsic positional features of a protein sequence.
This includes protein sequence feature annotation in any known sequence feature table format and any other report of protein features.
A map showing the relative positions of genetic markers in a nucleic acid sequence, based on estimation of non-physical distance such as recombination frequencies.
A genetic (linkage) map indicates the proximity of two genes on a chromosome, whether two genes are linked and the frequency they are transmitted together to an offspring. They are limited to genetic markers of traits observable only in whole organisms.
A map of genetic markers in a contiguous, assembled genomic sequence, with the sizes and separation of markers measured in base pairs.
A sequence map typically includes annotation on significant subsequences such as contigs, haplotypes and genes. The contigs shown will (typically) be a set of small overlapping clones representing a complete chromosomal segment.
A map of DNA (linear or circular) annotated with physical features or landmarks such as restriction sites, cloned DNA fragments, genes or genetic markers, along with the physical distances between them.
Distance in a physical map is measured in base pairs. A physical map might be ordered relative to a reference map (typically a genetic map) in the process of genome sequencing.
Image of a sequence with matches to signatures, motifs or profiles.
A map showing banding patterns derived from direct observation of a stained chromosome.
This is the lowest-resolution physical map and can provide only rough estimates of physical (base pair) distances. Like a genetic map, they are limited to genetic markers of traits observable only in whole organisms.
A gene map showing distances between loci based on relative cotransduction frequencies.
Sequence map of a single gene annotated with genetic features such as introns, exons, untranslated regions, polyA signals, promoters, enhancers and (possibly) mutations defining alleles of a gene.
Sequence map of a plasmid (circular DNA).
Image of the restriction enzyme cleavage sites (restriction sites) in a nucleic acid sequence.
Image showing matches between protein sequence(s) and InterPro Entries.
The sequence(s) might be screened against InterPro, or be the sequences from the InterPro entry itself. Each protein is represented as a scaled horizontal line with colored bars indicating the position of the matches.
Image showing detailed information on matches between protein sequence(s) and InterPro Entries.
The sequence(s) might be screened against InterPro, or be the sequences from the InterPro entry itself.
Image showing the architecture of InterPro domains in a protein sequence.
The sequence(s) might be screened against InterPro, or be the sequences from the InterPro entry itself. Domain architecture is shown as a series of non-overlapping domains in the protein.
Images based on GlobPlot prediction of intrinsic disordered regions and globular domains in protein sequences.
Report on the location of matches to profiles, motifs (conserved or functional patterns) or other signatures in one or more sequences.
Location of short repetitive subsequences (repeat sequences) in (typically nucleotide) sequences.
The report might include derived data map such as classification, annotation, organisation, periodicity etc.
regions of a nucleic acid sequence containing mobile genetic elements.
A report on quadruplex-forming motifs in a nucleotide sequence.
Report on nucleosome formation potential or exclusion sequence(s).
A report on exonic splicing enhancers (ESE) in an exon.
Gene features (exonic splicing enhancer)
A report on microRNA sequence (miRNA) or precursor, microRNA targets, miRNA binding sites in an RNA sequence etc.
protein-coding regions including coding sequences (CDS), exons, translation initiation sites and open reading frames.
A report on selenocysteine insertion sequence (SECIS) element in a DNA sequence.
transcription factor binding sites (TFBS) in a DNA sequence.
A report on predicted or known key residue positions (sites) in a protein sequence, such as binding or functional sites.
Use this concept for collections of specific sites which are not necessarily contiguous, rather than contiguous stretches of amino acids.
signal peptides or signal peptide cleavage sites in protein sequences.
Protein features report (signal peptides)
cleavage sites (for a proteolytic enzyme or agent) in a protein sequence.
Protein features report (cleavage sites)
post-translation modifications in a protein sequence, typically describing the specific sites involved.
Protein features (post-translation modifications)
catalytic residues (active site) of an enzyme.
ligand-binding (non-catalytic) residues of a protein, such as sites that bind metal, prosthetic groups or lipids.
A report on antigenic determinant sites (epitopes) in proteins, from sequence and / or structural data.
Epitope mapping is commonly done during vaccine design.
RNA and DNA-binding proteins and binding sites in protein sequences.
Protein features report (nucleic acid binding sites)
A report on epitopes that bind to MHC class I molecules.
A report on predicted epitopes that bind to MHC class II molecules.
A report or plot of PEST sites in a protein sequence.
'PEST' motifs target proteins for proteolytic degradation and reduce the half-lives of proteins dramatically.
Scores from a sequence database search (for example a BLAST search).
Alignments from a sequence database search (for example a BLAST search).
A report on the evaluation of the significance of sequence similarity scores from a sequence database search (for example a BLAST search).
Alphabet for the motifs (patterns) that MEME will search for.
File of directives for ordering and spacing of MEME motifs.
Dirichlet distribution used by hidden Markov model analysis programs.
Emission and transition counts of a hidden Markov model, generated once HMM has been determined, for example after residues/gaps have been assigned to match, delete and insert states.
Any specific or conserved pattern (typically expressed as a regular expression) in a molecular sequence.
Some type of statistical model representing a (typically multiple) sequence alignment.
An informative report about a specific or conserved protein sequence pattern.
A nucleotide regular expression pattern from the Prosite database.
A protein regular expression pattern from the Prosite database.
A profile (typically representing a sequence alignment) that is a simple matrix of nucleotide (or amino acid) counts per position.
A profile (typically representing a sequence alignment) that is weighted matrix of nucleotide (or amino acid) counts per position.
Contributions of individual sequences to the matrix might be uneven (weighted).
A profile (typically representing a sequence alignment) derived from a matrix of nucleotide (or amino acid) counts per position that reflects information content at each position.
A statistical Markov model of a system which is assumed to be a Markov process with unobserved (hidden) states. For example, a hidden Markov model representation of a set or alignment of sequences.
One or more fingerprints (sequence classifiers) as used in the PRINTS database.
A protein signature of the type used in the EMBASSY Signature package.
NULL hidden Markov model representation used by the HMMER package.
A protein family signature (sequence classifier) from the InterPro database.
Protein family signatures cover all domains in the matching proteins and span >80% of the protein length and with no adjacent protein domain signatures or protein region signatures.
A protein domain signature (sequence classifier) from the InterPro database.
Protein domain signatures identify structural or functional domains or other units with defined boundaries.
A protein region signature (sequence classifier) from the InterPro database.
A protein region signature defines a region which cannot be described as a protein family or domain signature.
A protein repeat signature (sequence classifier) from the InterPro database.
A protein repeat signature is a repeated protein motif, that is not in single copy expected to independently fold into a globular domain.
A protein site signature (sequence classifier) from the InterPro database.
A protein site signature is a classifier for a specific site in a protein.
A protein conserved site signature (sequence classifier) from the InterPro database.
A protein conserved site signature is any short sequence pattern that may contain one or more unique residues and is cannot be described as a active site, binding site or post-translational modification.
A protein active site signature (sequence classifier) from the InterPro database.
A protein active site signature corresponds to an enzyme catalytic pocket. An active site typically includes non-contiguous residues, therefore multiple signatures may be required to describe an active site. ; residues involved in enzymatic reactions for which mutational data is typically available.
A protein binding site signature (sequence classifier) from the InterPro database.
A protein binding site signature corresponds to a site that reversibly binds chemical compounds, which are not themselves substrates of the enzymatic reaction. This includes enzyme cofactors and residues involved in electron transport or protein structure modification.
A protein post-translational modification signature (sequence classifier) from the InterPro database.
A protein post-translational modification signature corresponds to sites that undergo modification of the primary structure, typically to activate or de-activate a function. For example, methylation, sumoylation, glycosylation etc. The modification might be permanent or reversible.
Protein post-translational modification signature
Alignment of exactly two molecular sequences.
Alignment of more than two molecular sequences.
Alignment of multiple nucleotide sequences.
Alignment of multiple protein sequences.
Alignment of multiple molecular sequences of different types.
Hybrid sequence alignments include for example genomic DNA to EST, cDNA or mRNA.
Alignment of exactly two nucleotide sequences.
Alignment of exactly two protein sequences.
Alignment of exactly two molecular sequences of different types.
Alignment of more than two nucleotide sequences.
Alignment of more than two protein sequences.
A simple floating point number defining the penalty for opening or extending a gap in an alignment.
Controls the order of sequences in an output sequence alignment.
A penalty for opening a gap in an alignment.
A penalty for extending a gap in an alignment.
A penalty for gaps that are close together in an alignment.
A penalty for gaps at the termini of an alignment, either from the N/C terminal of protein or 5'/3' terminal of nucleotide sequences.
The score for a 'match' used in various sequence database search applications with simple scoring schemes.
The score (penalty) for a 'mismatch' used in various alignment and sequence database search applications with simple scoring schemes.
This is the threshold drop in score at which extension of word alignment is halted.
A simple floating point number defining the penalty for opening a gap in an alignment.
A simple floating point number defining the penalty for extending a gap in an alignment.
A simple floating point number defining the penalty for gaps that are close together in an alignment.
A number defining the penalty for opening gaps at the termini of an alignment, either from the N/C terminal of protein or 5'/3' terminal of nucleotide sequences.
A number defining the penalty for extending gaps at the termini of an alignment, either from the N/C terminal of protein or 5'/3' terminal of nucleotide sequences.
Sequence identity is the number (%) of matches (identical characters) in positions from an alignment of two molecular sequences.
Sequence similarity is the similarity (expressed as a percentage) of two molecular sequences calculated from their alignment, a scoring matrix for scoring characters substitutions and penalties for gap insertion and extension.
Data on molecular sequence alignment quality (estimated accuracy).
Sequence alignment metadata (quality report)
Data on character conservation in a molecular sequence alignment.
This is a broad data type and is used a placeholder for other, more specific types. It is primarily intended to help navigation of EDAM and would not typically be used for annotation. Use this concept for calculated substitution rates, relative site variability, data on sites with biased properties, highly conserved or very poorly conserved sites, regions, blocks etc.
Sequence alignment report (site conservation)
Data on correlations between sites in a molecular sequence alignment, typically to identify possible covarying positions and predict contacts or structural constraints in protein structures.
Sequence alignment report (site correlation)
Alignment of molecular sequences to a Domainatrix signature (representing a sequence alignment).
Sequence-profile alignment (Domainatrix signature)
Alignment of molecular sequence(s) to a hidden Markov model(s).
Alignment of molecular sequences to a protein fingerprint from the PRINTS database.
Sequence-profile alignment (fingerprint)
Continuous quantitative data that may be read during phylogenetic tree calculation.
Phylogenetic continuous quantitative characters
Phylogenetic continuous quantitative data
Character data with discrete states that may be read during phylogenetic tree calculation.
One or more cliques of mutually compatible characters that are generated, for example from analysis of discrete character data, and are used to generate a phylogeny.
Phylogenetic invariants data for testing alternative tree topologies.
A report of data concerning or derived from a phylogenetic tree, or from comparing two or more phylogenetic trees.
This is a broad data type and is used for example for reports on confidence, shape or stratigraphic (age) data derived from phylogenetic tree analysis.
A model of DNA substitution that explains a DNA sequence alignment, derived from phylogenetic tree analysis.
Phylogenetic tree report (DNA substitution model)
Sequence alignment report (DNA substitution model)
Data about the shape of a phylogenetic tree.
Data on the confidence of a phylogenetic tree.
Phylogenetic tree report (tree evaluation)
Distances, such as Branch Score distance, between two or more phylogenetic trees.
Phylogenetic tree report (tree distances)
Molecular clock and stratigraphic (age) data derived from phylogenetic tree analysis.
Phylogenetic tree report (tree stratigraphic)
Independent contrasts for characters used in a phylogenetic tree, or covariances, regressions and correlations between characters for those contrasts.
Phylogenetic report (character contrasts)
Matrix of integer numbers for sequence comparison.
Matrix of floating point numbers for sequence comparison.
Matrix of integer or floating point numbers for nucleotide comparison.
Matrix of integer or floating point numbers for amino acid comparison.
Matrix of integer numbers for nucleotide comparison.
Nucleotide substitution matrix (integers)
Matrix of floating point numbers for nucleotide comparison.
Matrix of integer numbers for amino acid comparison.
Matrix of floating point numbers for amino acid comparison.
3D coordinate and associated data for a nucleic acid tertiary (3D) structure.
3D coordinate and associated data for a protein tertiary (3D) structure, or part of a structure, possibly in complex with other molecules.
The structure of a protein in complex with a ligand, typically a small molecule such as an enzyme substrate or cofactor, but possibly another macromolecule.
This includes interactions of proteins with atoms, ions and small molecules or macromolecules such as nucleic acids or other polypeptides. For stable inter-polypeptide interactions use 'Protein complex' instead.
3D coordinate and associated data for a carbohydrate (3D) structure.
3D coordinate and associated data for the (3D) structure of a small molecule, such as any common chemical compound.
3D coordinate and associated data for a DNA tertiary (3D) structure.
3D coordinate and associated data for an RNA tertiary (3D) structure.
3D coordinate and associated data for a tRNA tertiary (3D) structure, including tmRNA, snoRNAs etc.
3D coordinate and associated data for the tertiary (3D) structure of a polypeptide chain.
3D coordinate and associated data for the tertiary (3D) structure of a protein domain.
3D coordinate and associated data for a protein tertiary (3D) structure (all atoms).
3D coordinate and associated data for a protein tertiary (3D) structure (typically C-alpha atoms only).
C-beta atoms from amino acid side-chains may be included.
3D coordinate and associated data for a polypeptide chain tertiary (3D) structure (all atoms).
3D coordinate and associated data for a polypeptide chain tertiary (3D) structure (typically C-alpha atoms only).
3D coordinate and associated data for a protein domain tertiary (3D) structure (all atoms).
3D coordinate and associated data for a protein domain tertiary (3D) structure (typically C-alpha atoms only).
Alignment (superimposition) of exactly two molecular tertiary (3D) structures.
Alignment (superimposition) of more than two molecular tertiary (3D) structures.
Alignment (superimposition) of protein tertiary (3D) structures.
Alignment (superimposition) of nucleic acid tertiary (3D) structures.
Alignment (superimposition) of exactly two protein tertiary (3D) structures.
Alignment (superimposition) of more than two protein tertiary (3D) structures.
Multiple protein tertiary structure alignment
Alignment (superimposition) of protein tertiary (3D) structures (all atoms considered).
Alignment (superimposition) of protein tertiary (3D) structures (typically C-alpha atoms only considered).
C-beta atoms from amino acid side-chains may be considered.
Structure alignment (protein C-alpha atoms)
Alignment (superimposition) of exactly two protein tertiary (3D) structures (all atoms considered).
Pairwise protein tertiary structure alignment (all atoms)
Alignment (superimposition) of exactly two protein tertiary (3D) structures (typically C-alpha atoms only considered).
Pairwise protein tertiary structure alignment (C-alpha atoms)
Multiple protein tertiary structure alignment (all atoms)
Multiple protein tertiary structure alignment (C-alpha atoms)
Alignment (superimposition) of exactly two nucleic acid tertiary (3D) structures.
Alignment (superimposition) of more than two nucleic acid tertiary (3D) structures.
Multiple nucleic acid tertiary structure alignment
Alignment (superimposition) of RNA tertiary (3D) structures.
Matrix to transform (rotate/translate) 3D coordinates, typically the transformation necessary to superimpose two molecular structures.
DaliLite hit table of protein chain tertiary structure alignment data.
The significant and top-scoring hits for regions of the compared structures is shown. Data such as Z-Scores, number of aligned residues, root-mean-square deviation (RMSD) of atoms and sequence identity are given.
A score reflecting structural similarities of two molecules.
Root-mean-square deviation (RMSD) is calculated to measure the average distance between superimposed macromolecular coordinates.
A measure of the similarity between two ligand fingerprints.
A ligand fingerprint is derived from ligand structural data from a Protein DataBank file. It reflects the elements or groups present or absent, covalent bonds and bond orders and the bonded environment in terms of SATIS codes and BLEEP atom types.
A matrix of 3D-1D scores reflecting the probability of amino acids to occur in different tertiary structural environments.
A table of 20 numerical values which quantify a property (e.g. physicochemical or biochemical) of the common amino acids.
Chemical classification (small, aliphatic, aromatic, polar, charged etc) of amino acids.
Contact potentials (amino acid pair-wise)
Hydrophobic, hydrophilic or charge properties of amino acids.
Experimental free energy values for the water-interface and water-octanol transitions for the amino acids.
Van der Waals radii of atoms for different amino acid residues.
An informative report on a specific enzyme.
An informative report on a specific restriction enzyme such as enzyme reference data.
This might include name of enzyme, organism, isoschizomers, methylation, source, suppliers, literature references, or data on restriction enzyme patterns such as name of enzyme, recognition site, length of pattern, number of cuts made by enzyme, details of blunt or sticky end cut etc.
List of molecular weight(s) of one or more proteins or peptides, for example cut by proteolytic enzymes or reagents.
The report might include associated data such as frequency of peptide fragment molecular weights.
Report on the hydrophobic moment of a polypeptide sequence.
Hydrophobic moment is a peptides hydrophobicity measured for different angles of rotation.
The aliphatic index is the relative protein volume occupied by aliphatic side chains.
A protein sequence with annotation on hydrophobic or hydrophilic / charged regions, hydrophobicity plot etc.
A plot of the mean charge of the amino acids within a window of specified length as the window is moved along a protein sequence.
The solubility or atomic solvation energy of a protein sequence or structure.
Data on the crystallizability of a protein sequence.
Data on the stability, intrinsic disorder or globularity of a protein sequence.
The hydrogen exchange rate of a protein.
The extinction coefficient of a protein.
An informative report on protein subcellular localisation (nuclear, cytoplasmic, mitochondrial, chloroplast, plastid, membrane etc) or destination (exported / extracellular proteins).
Protein report (subcellular localisation)
An report on allergenicity / immunogenicity of peptides and proteins.
This includes data on peptide ligands that elicit an immune response (immunogens), allergic cross-reactivity, predicted antigenicity (Hopp and Woods plot) etc. These data are useful in the development of peptide-specific antibodies or multi-epitope vaccines. Methods might use sequence data (for example motifs) and / or structural data.
A report on the immunogenicity of MHC class I or class II binding peptides.
A human-readable collection of information about one or more specific protein 3D structure(s) or structural domains.
Report on the quality of a protein three-dimensional model.
Protein structure report (quality evaluation)
Model validation might involve checks for atomic packing, steric clashes, agreement with electron density maps etc.
Data on inter-atomic or inter-residue contacts, distances and interactions in protein structure(s) or on the interactions of protein atoms or residues with non-protein groups.
Informative report on flexibility or motion of a protein structure.
Data on the solvent accessible or buried surface area of a protein structure.
This concept covers definitions of the protein surface, interior and interfaces, accessible and buried residues, surface accessible pockets, interior inaccessible cavities etc.
Data on the surface properties (shape, hydropathy, electrostatic patches etc) of a protein structure.
Phi/psi angle data or a Ramachandran plot of a protein structure.
Data on the net charge distribution (dipole moment) of a protein structure.
A matrix of distances between amino acid residues (for example the C-alpha atoms) in a protein structure.
An amino acid residue contact map for a protein structure.
Report on clusters of contacting residues in protein structures such as a key structural residue network.
Patterns of hydrogen bonding in protein structures.
Non-canonical atomic interactions in protein structures.
Information on a node from the CATH database.
The report (for example http://www.cathdb.info/cathnode/1.10.10.10) includes CATH code (of the node and upper levels in the hierarchy), classification text (of appropriate levels in hierarchy), list of child nodes, representative domain and other relevant data and links.
Information on a node from the SCOP database.
An EMBASSY domain classification file (DCF) of classification and other data for domains from SCOP or CATH, in EMBL-like format.
Information on a protein 'class' node from the CATH database.
Information on a protein 'architecture' node from the CATH database.
Information on a protein 'topology' node from the CATH database.
Information on a protein 'homologous superfamily' node from the CATH database.
Information on a protein 'structurally similar group' node from the CATH database.
Information on a protein 'functional category' node from the CATH database.
A report on known protein structural domains or folds that are recognised (identified) in protein sequence(s).
Methods use some type of mapping between sequence and fold, for example secondary structure prediction and alignment, profile comparison, sequence properties, homologous sequence search, kernel machines etc. Domains and folds might be taken from SCOP or CATH.
protein-protein interaction(s), including interactions between protein domains.
An informative report on protein-ligand (small molecule) interaction(s).
Protein-nucleic acid interactions report
Nucleic acid melting curve: a melting curve of a double-stranded nucleic acid molecule (DNA or DNA/RNA). Shows the proportion of nucleic acid which are double-stranded versus temperature.
Nucleic acid probability profile: a probability profile of a double-stranded nucleic acid molecule (DNA or DNA/RNA). Shows the probability of a base pair not being melted (i.e. remaining as double-stranded DNA) at a specified temperature
Nucleic acid stitch profile: stitch profile of hybridised or double stranded nucleic acid (DNA or RNA/DNA). A stitch profile diagram shows partly melted DNA conformations (with probabilities) at a range of temperatures. For example, a stitch profile might show possible loop openings with their location, size, probability and fluctuations at a given temperature.
Nucleic acid temperature profile: a temperature profile of a double-stranded nucleic acid molecule (DNA or DNA/RNA). Plots melting temperature versus base position.
Data on the dissociation characteristics of a double-stranded nucleic acid molecule (DNA or a DNA/RNA hybrid) during heating.
A melting (stability) profile calculated the free energy required to unwind and separate the nucleic acid strands, plotted for sliding windows over a sequence.
Enthalpy of hybridised or double stranded nucleic acid (DNA or RNA/DNA).
Entropy of hybridised or double stranded nucleic acid (DNA or RNA/DNA).
Melting temperature of hybridised or double stranded nucleic acid (DNA or RNA/DNA).
Stitch profile of hybridised or double stranded nucleic acid (DNA or RNA/DNA).
RNA parameters used by the Vienna package.
Structure constraints used by the Vienna package.
RNA concentration data used by the Vienna package.
RNA calculated energy data generated by the Vienna package.
Dotplot of RNA base pairing probability matrix.
Such as generated by the Vienna package.
A human-readable collection of information about RNA/DNA folding, minimum folding energies for DNA or RNA sequences, energy landscape of RNA mutants etc.
RNA secondary structure folding classification
RNA secondary structure folding probablities
Table of codon usage data calculated from one or more nucleic acid sequences.
A codon usage table might include the codon usage table name, optional comments and a table with columns for codons and corresponding codon usage data. A genetic code can be extracted from or represented by a codon usage table.
A genetic code need not include detailed codon usage information.
A simple measure of synonymous codon usage bias often used to predict gene expression levels.
A plot of the synonymous codon usage calculated for windows over a nucleotide sequence.
The effective number of codons used in a gene sequence. This reflects how far codon usage of a gene departs from equal usage of synonymous codons.
The differences in codon usage fractions between two codon usage tables.
A human-readable collection of information about the influence of genotype on drug response.
The report might correlate gene expression or single-nucleotide polymorphisms with drug efficacy or toxicity.
A human-readable collection of information about a specific disease.
For example, an informative report on a specific tumor including nature and origin of the sample, anatomic site, organ or tissue, tumor type, including morphology and/or histologic type, and so on.
A report on linkage disequilibrium; the non-random association of alleles or polymorphisms at two or more loci (not necessarily on the same chromosome).
A graphical 2D tabular representation of expression data, typically derived from an omics experiment. A heat map is a table where rows and columns correspond to different features and contexts (for example, cells or samples) and the cell colour represents the level of expression of a gene that context.
Affymetrix library file of information about which probes belong to which probe set.
Affymetrix library file of information about the probe sets such as the gene name with which the probe set is associated.
Affymetrix probe sets information library file
Standard protonated molecular masses from trypsin (modified porcine trypsin, Promega) and keratin peptides, used in EMBOSS.
A report typically including a map (diagram) of a metabolic pathway.
This includes carbohydrate, energy, lipid, nucleotide, amino acid, glycan, PK/NRP, cofactor/vitamin, secondary metabolite, xenobiotics etc.
genetic information processing pathways.
Genetic information processing pathway report
environmental information processing pathways.
Environmental information processing pathway report
A report typically including a map (diagram) of a signal transduction pathway.
Topic concernning cellular process pathways.
disease pathways, typically of human disease.
A report typically including a map (diagram) of drug structure relationships.
An entry (data type) from the Minimal Information Requested in the Annotation of Biochemical Models (MIRIAM) database of data resources.
A MIRIAM entry describes a MIRIAM data type including the official name, synonyms, root URI, identifier pattern (regular expression applied to a unique identifier of the data type) and documentation. Each data type can be associated with several resources. Each resource is a physical location of a service (typically a database) providing information on the elements of a data type. Several resources may exist for each data type, provided the same (mirrors) or different information. MIRIAM provides a stable and persistent reference to its data types.
A simple floating point number defining the lower or upper limit of an expectation value (E-value).
An expectation value (E-Value) is the expected number of observations which are at least as extreme as observations expected to occur by random chance. The E-value describes the number of hits with a given score or better that are expected to occur at random when searching a database of a particular size. It decreases exponentially with the score (S) of a hit. A low E value indicates a more significant score.
The z-value is the number of standard deviations a data value is above or below a mean value.
A z-value might be specified as a threshold for reporting hits from database searches.
The P-value is the probability of obtaining by random chance a result that is at least as extreme as an observed result, assuming a NULL hypothesis is true.
Information on a database (or ontology) version, for example name, version number and release date.
Information on an application version, for example name, version number and release date.
Information on a version of the CATH database.
Cross-mapping of Swiss-Prot codes to PDB identifiers.
Cross-references from a sequence record to other databases.
Metadata on the status of a submitted job.
Values for EBI services are 'DONE' (job has finished and the results can then be retrieved), 'ERROR' (the job failed or no results where found), 'NOT_FOUND' (the job id is no longer available; job results might be deleted, 'PENDING' (the job is in a queue waiting processing), 'RUNNING' (the job is currently being processed).
The (typically numeric) unique identifier of a submitted job.
A label (text token) describing the type of job, for example interactive or non-interactive.
A report of tool-specific metadata on some analysis or process performed, for example a log of diagnostic or error messages.
DaliLite log file describing all the steps taken by a DaliLite alignment of two protein structures.
EMBOSS (EMBASSY) domainatrix application log file.
EMBOSS (EMBASSY) sites application log file.
EMBOSS (EMBASSY) supermatcher error file.
Number of entities (for example database hits, sequences, alignments etc) to write to an output file.
Controls the order of hits (reported matches) in an output file from a database search.
A drug structure relationship map is report (typically a map diagram) of drug structure relationships.
A human-readable collection of information about a specific drug.
An image (for viewing or printing) of a phylogenetic tree including (typically) a plot of rooted or unrooted phylogenies, cladograms, circular trees or phenograms and associated information.
Image of RNA secondary structure, knots, pseudoknots etc.
Image of one or more molecular tertiary (3D) structures.
Image of two or more aligned molecular sequences possibly annotated with alignment features.
An image of the structure of a small chemical compound.
The molecular identifier and formula are typically included.
A fate map is a plan of early stage of an embryo such as a blastula, showing areas that are significance to development.
An image of spots from a microarray experiment.
A term definition from The Gene Ontology (GO).
A term from the HGNC controlled vocabulary.
A term from the NCBI taxonomy vocabulary.
A term from Foundational Model of Anatomy.
A term definition for a biological process from the Gene Ontology (GO).
A term definition for a molecular function from the Gene Ontology (GO).
A term definition for a cellular component from the Gene Ontology (GO).
The definition of a concept from an ontology.
A comment on a concept from an ontology.
Reference for a concept from an ontology.
Information on a published article provided by the doc2loc program.
The doc2loc output includes the url, format, type and availability code of a document for every service provider.
A residue identifier (a string) from a PDB file.
Cartesian coordinate of an atom (in a molecular structure).
Cartesian x coordinate of an atom (in a molecular structure).
Cartesian y coordinate of an atom (in a molecular structure).
Cartesian z coordinate of an atom (in a molecular structure).
Identifier (a string) of a specific atom from a PDB file for a molecular structure.
Data on a single atom from a protein structure.
Data on a single amino acid residue position in a protein structure.
Three-letter amino acid residue names as used in PDB files.
Identifier of a model structure from a PDB file.
Summary of domain classification information for a CATH domain.
The report (for example http://www.cathdb.info/domain/1cukA01) includes CATH codes for levels in the hierarchy for the domain, level descriptions and relevant data and links.
FASTA sequence database (based on ATOM records in PDB) for CATH domains (clustered at different levels of sequence identity).
CATH representative domain sequences (ATOM)
FASTA sequence database (based on COMBS sequence data) for CATH domains (clustered at different levels of sequence identity).
CATH representative domain sequences (COMBS)
FASTA sequence database for all CATH domains (based on PDB ATOM records).
FASTA sequence database for all CATH domains (based on COMBS sequence data).
Information on an molecular sequence version.
A numerical value, that is some type of scored value arising for example from a prediction method.
Report on general functional properties of specific protein(s).
For properties that can be mapped to a sequence, use 'Sequence report' instead.
Name of a gene from Aspergillus Genome Database.
Name of a gene from Candida Genome Database.
Primary name of a gene from EcoGene Database.
Name of a gene from MaizeGDB (maize genes) database.
Name of a gene from Saccharomyces Genome Database.
Name of a gene from Tetrahymena Genome Database.
http://www.geneontology.org/doc/GO.xrf_abbs: CGSC
Symbol of a gene from E.coli Genetic Stock Center.
http://www.geneontology.org/doc/GO.xrf_abbs: HGNC_gene
Symbol of a gene approved by the HUGO Gene Nomenclature Committee.
http://www.geneontology.org/doc/GO.xrf_abbs: MGD
Symbol of a gene from the Mouse Genome Database.
http://www.geneontology.org/doc/GO.xrf_abbs: SUBTILISTG
Symbol of a gene from Bacillus subtilis Genome Sequence Project.
http://www.geneontology.org/doc/GO.xrf_abbs: ApiDB_PlasmoDB
Identifier of a gene from PlasmoDB Plasmodium Genome Resource.
Identifier of a gene from EcoGene Database.
http://www.geneontology.org/doc/GO.xrf_abbs: FB
http://www.geneontology.org/doc/GO.xrf_abbs: FlyBase
Gene identifier from Glossina morsitans GeneDB database.
Gene identifier from Leishmania major GeneDB database.
http://www.geneontology.org/doc/GO.xrf_abbs: GeneDB_Pfalciparum
Gene identifier from Plasmodium falciparum GeneDB database.
http://www.geneontology.org/doc/GO.xrf_abbs: GeneDB_Spombe
Gene identifier from Schizosaccharomyces pombe GeneDB database.
Gene ID (GeneDB Schizosaccharomyces pombe)
http://www.geneontology.org/doc/GO.xrf_abbs: GeneDB_Tbrucei
Gene identifier from Trypanosoma brucei GeneDB database.
http://www.geneontology.org/doc/GO.xrf_abbs: GR_GENE
http://www.geneontology.org/doc/GO.xrf_abbs: PAMGO_VMD
http://www.geneontology.org/doc/GO.xrf_abbs: VMD
Gene identifier from Virginia Bioinformatics Institute microbial database.
http://www.geneontology.org/doc/GO.xrf_abbs: SGN
Gene identifier from Sol Genomics Network.
http://www.geneontology.org/doc/GO.xrf_abbs: WB
http://www.geneontology.org/doc/GO.xrf_abbs: WormBase
Gene identifier used by WormBase database.
Any name (other than the recommended one) for a gene.
The name of an open reading frame attributed by a sequencing project.
A component of a larger sequence assembly.
A report on a chromosome aberration such as abnormalities in chromosome structure.
An identifier of a clone (cloned molecular sequence) from a database.
An insertion code (part of the residue number) for an amino acid residue from a PDB file.
The fraction of an atom type present at a site in a molecular structure.
The sum of the occupancies of all the atom types at a site should not normally significantly exceed 1.0.
Isotropic B factor (atomic displacement parameter) for an atom from a PDB file.
A cytogenetic map showing chromosome banding patterns in mutant cell lines relative to the wild type.
A cytogenetic map is built from a set of mutant cell lines with sub-chromosomal deletions and a reference wild-type line ('genome deletion panel'). The panel is used to map markers onto the genome by comparing mutant to wild-type banding patterns. Markers are linked (occur in the same deleted region) if they share the same banding pattern (presence or absence) as the deletion panel.
A genetic map which shows the approximate location of quantitative trait loci (QTL) between two or more markers.
A map of haplotypes in a genome or other sequence, describing common patterns of genetic variation.
Data describing a set of multiple genetic or physical maps, typically sharing a common set of features which are mapped.
A feature which may mapped (positioned) on a genetic or other type of map.
Mappable features may be based on Gramene's notion of map features; see http://www.gramene.org/db/cmap/feature_type_info.
A designation of the type of map (genetic map, physical map, sequence map etc) or map set.
Map types may be based on Gramene's notion of a map type; see http://www.gramene.org/db/cmap/map_type_info.
The name of a group of organisms belonging to the same taxonomic rank.
For a complete list of taxonomic ranks see https://www.phenoscape.org/wiki/Taxonomic_Rank_Vocabulary.
A unique identifier of a (group of) organisms.
The full name for a group of organisms, reflecting their biological classification and (usually) conforming to a standard nomenclature.
Name components correspond to levels in a taxonomic hierarchy (e.g. 'Genus', 'Species', etc.) Meta information such as a reference where the name was defined and a date might be included.
A unique identifier for an organism used in the iHOP database.
Common name for an organism as used in the GenBank database.
The name of a taxon from the NCBI taxonomy database.
A term which is likely to be misleading of its meaning.
Information on the authors of a published work.
An identifier representing an author in the DragonDB database.
A URI along with annotation describing the data found at the address.
A controlled vocabulary for words and phrases that can appear in the keywords field (KW line) of entries from the UniProt database.
Identifier of a gene from the GeneFarm database.
Identifier for genetic elements in MIPS Maize database.
Identifier for genetic elements in MIPS Medicago database.
The name of an Antirrhinum Gene from the DragonDB database.
A unique identifier for an Arabidopsis gene, which is an acronym or abbreviation of the gene name.
A unique identifier of a protein or gene used in the iHOP database.
Name of a gene from the GeneFarm database.
A unique name or other identifier of a genetic locus, typically conforming to a scheme that names loci (such as predicted genes) depending on their position in a molecular sequence, for example a completely sequenced genome or chromosome.
Locus identifier for Arabidopsis Genome Initiative (TAIR, TIGR and MIPS databases)
http://www.geneontology.org/doc/GO.xrf_abbs: ASPGD
http://www.geneontology.org/doc/GO.xrf_abbs: ASPGDID
Identifier for loci from ASPGD (Aspergillus Genome Database).
http://www.geneontology.org/doc/GO.xrf_abbs: Broad_MGG
Identifier for loci from Magnaporthe grisea Database at the Broad Institute.
http://www.geneontology.org/doc/GO.xrf_abbs: CGD
http://www.geneontology.org/doc/GO.xrf_abbs: CGDID
Identifier for loci from CGD (Candida Genome Database).
http://www.geneontology.org/doc/GO.xrf_abbs: JCVI_CMR
http://www.geneontology.org/doc/GO.xrf_abbs: TIGR_CMR
Locus identifier for Comprehensive Microbial Resource at the J. Craig Venter Institute.
http://www.geneontology.org/doc/GO.xrf_abbs: NCBI_locus_tag
http://www.geneontology.org/doc/GO.xrf_abbs: SGD
http://www.geneontology.org/doc/GO.xrf_abbs: SGDID
Identifier for loci from SGD (Saccharomyces Genome Database).
Identifier of loci from Maize Mapping Project.
Identifier of locus from DictyBase (Dictyostelium discoideum).
Identifier of a locus from EntrezGene database.
Identifier of locus from MaizeGDB (Maize genome database).
A stretch of DNA that is closely linked to the genes underlying a quantitative trait (a phenotype that varies in degree and depends upon the interactions between multiple genes and their environment).
A QTL sometimes but does not necessarily correspond to a gene.
Identifier of a gene from the KOME database.
Identifier of a locus from the Tropgene database.
An alignment of molecular sequences, structures or profiles derived from them.
Data for an atom (in a molecular structure).
http://www.geneontology.org/doc/GO.xrf_abbs: SP_KW
A word or phrase that can appear in the keywords field (KW line) of entries from the UniProt database.
A name for a genetic locus conforming to a scheme that names loci (such as predicted genes) depending on their position in a molecular sequence, for example a completely sequenced genome or chromosome.
A position in a map (for example a genetic map), either a single position (point) or a region / interval.
This includes positions in genomes based on a reference sequence. A position may be specified for any mappable object, i.e. anything that may have positional information such as a physical position in a chromosome. Data might include sequence region name, strand, coordinate system name, assembly name, start position and end position.
Data concerning the intrinsic physical (e.g. structural) or chemical properties of one, more or all amino acids.
A human-readable collection of information which (typically) is generated or collated by hand and which describes a biological entity, phenomena or associated primary (e.g. sequence or structural) data, as distinct from the primary data itself and computer-generated reports derived from it.
Data describing a molecular map (genetic or physical) or a set of such maps, including various attributes of, data extracted from or derived from the analysis of them, but exluding the map(s) themselves. This includes metadata for map sets that share a common set of features which are mapped.
Data used by the Vienna RNA analysis package.
Data used to replace (mask) characters in a molecular sequence.
Data concerning chemical reaction(s) catalysed by enzyme(s).
A plot giving an approximation of the kinetics of an enzyme-catalysed reaction, assuming simple kinetics (i.e. no intermediate or product inhibition, allostericity or cooperativity). It plots initial reaction rate to the substrate concentration (S) from which the maximum rate (vmax) is apparent.
A plot based on the Michaelis Menten equation of enzyme kinetics plotting the ratio of the initial substrate concentration (S) against the reaction velocity (v).
Raw data from or annotation on laboratory experiments.
Typically a human-readable summary of body of facts or information indicating why a statement is true or valid. This may include a computational prediction, laboratory experiment, literature reference etc.
A molecular sequence and minimal metadata, typically an identifier of the sequence and/or a comment.
One or more molecular sequences, possibly with associated annotation.
This concept is a placeholder of concepts for primary sequence data including raw sequences and sequence records. It should not normally be used for derivatives such as sequence alignments, motifs or profiles.
A nucleic acid sequence and minimal metadata, typically an identifier of the sequence and/or a comment.
A protein sequence and minimal metadata, typically an identifier of the sequence and/or a comment.
A human-readable collection of information including annotation on a biological entity or phenomena, computer-generated reports of analysis of primary data (e.g. sequence or structural), and metadata (data about primary data) or any other free (essentially unformatted) text, as distinct from the primary data itself.
You can use this term by default for any textual report, in case you can't find another, more specific term. Reports may be generated automatically or collated by hand and can include metadata on the origin, source, history, ownership or location of some thing.
Data concerning molecular structural data.
Some simple value controlling a search operation, typically a search of a database.
A report of hits from searching a database of some type.
The secondary structure assignment (predicted or real) of a nucleic acid or protein.
Data concerning, extracted from, or derived from the analysis of molecular alignment of some type.
A human-readable collection of information about one or more specific nucleic acid molecules.
A human-readable collection of information about one or more molecular tertiary (3D) structures. It might include annotation on the structure, a computer-generated report of analysis of structural data, and metadata (data about primary data) or any other free (essentially unformatted) text, as distinct from the primary data itself.
A report on nucleic acid structure-derived data, describing structural properties of a DNA molecule, or any other annotation or information about specific nucleic acid 3D structure(s).
A report on the physical (e.g. structural) or chemical properties of molecules, or parts of a molecule.
Structural data for DNA base pairs or runs of bases, such as energy or angle data.
Information on a database (or ontology) entry version, such as name (or other identifier) or parent database, unique identifier of entry, data, author and so on.
A persistent (stable) and unique identifier, typically identifying an object (entry) from a database.
single nucleotide polymorphism (SNP) in a DNA sequence.
Reference to a dataset (or a cross-reference between two datasets), typically one or more entries in a biological database or ontology.
A list of database accessions or identifiers are usually included.
A name of a thing, which need not necessarily uniquely identify it.
Closely related, but focusing on labeling and human readability but not on identification.
A label (text token) describing the type of a thing, typically an enumerated string (a string with one of a limited set of values).
An identifier of a software end-user (typically a person).
A three-letter code used in the KEGG databases to uniquely identify organisms.
Name of an entry (gene) from the KEGG GENES database.
Identifier of an object from one of the BioCyc databases.
Identifier of a compound from the BioCyc chemical compounds database.
Identifier of a biological reaction from the BioCyc reactions database.
Identifier of an enzyme from the BioCyc enzymes database.
Identifier of a biological reaction from a database.
An identifier that is re-used for data objects of fundamentally different types (typically served from a single database).
This branch provides an alternative organisation of the concepts nested under 'Accession' and 'Name'. All concepts under here are already included under 'Accession' or 'Name'.
Identifier of a codon usage table, for example a genetic code.
Primary identifier of an object from the FlyBase database.
Identifier of an object from the WormBase database.
Protein identifier used by WormBase database.
An informative report on a trinucleotide sequence that encodes an amino acid including the triplet sequence, the encoded amino acid or whether it is a start or stop codon.
An identifier of a map of a molecular sequence.
Name or other identifier of a nucleic acid molecule.
Frame for translation of DNA (3 forward and 3 reverse frames relative to a chromosome).
Informal name for a genetic code, typically an organism name.
Name of a file format such as HTML, PNG, PDF, EMBL, GenBank and so on.
A label (text token) describing a type of sequence profile such as frequency matrix, Gribskov profile, hidden Markov model etc.
Name of a computer operating system such as Linux, PC or Mac.
A type of point or block mutation, including insertion, deletion, change, duplication and moves.
A logical operator such as OR, AND, XOR, and NOT.
A control of the order of data that is output, for example the order of sequences in an alignment.
Possible options including sorting by score, rank, by increasing P-value (probability, i.e. most statistically significant hits given first) and so on.
A simple parameter that is a toggle (boolean value), typically a control for a modal tool.
The width of an output sequence or alignment.
A penalty for introducing or extending a gap in an alignment.
A temperature concerning nucleic acid denaturation, typically the temperature at which the two strands of a hybridised or double stranded nucleic acid (DNA or RNA/DNA) molecule separate.
The concentration of a chemical compound.
Size of the incremental 'step' a sequence window is moved over a sequence.
An image of a graph generated by the EMBOSS suite.
An application report generated by the EMBOSS suite.
An offset for a single-point sequence position.
A value that serves as a threshold for a tool (usually to control scoring or output).
An informative report on a transcription factor protein.
This might include conformational or physicochemical properties, as well as sequence information for transcription factor(s) binding sites.
The name of a category of biological or bioinformatics database.
A parameter that is used to control rendering (drawing) to a device or image.
Any arbitrary name of a molecular sequence.
Word composition data for a molecular sequence.
A plot of Fickett testcode statistic (identifying protein coding regions) in a nucleotide sequences.
A plot of sequence similarities identified from word-matching or character comparison.
Use this concept for calculated substitution rates, relative site variability, data on sites with biased properties, highly conserved or very poorly conserved sites, regions, blocks etc.
An image of peptide sequence sequence looking down the axis of the helix for highlighting amphipathicity and other properties.
An image of peptide sequence sequence in a simple 3,4,3,4 repeating pattern that emulates at a simple level the arrangement of residues around an alpha helix.
Useful for highlighting amphipathicity and other properties.
A plot of general physicochemical properties of a protein sequence.
A plot of character or word composition / frequency of a molecular sequence.
Density plot (of base composition) for a nucleotide sequence.
Image of a sequence trace (nucleotide sequence versus probabilities of each of the 4 bases).
A collection of multiple molecular sequences and (typically) associated metadata that is intended for sequential processing.
This concept may be used for sequence sets that are expected to be read and processed a single sequence at a time.
Secondary identifier of an object from the FlyBase database.
Secondary identifier are used to handle entries that were merged with or split from other entries in the database.
A fixed-size datum calculated (by using a hash function) for a molecular sequence, typically for purposes of error detection or indexing.
Protein features report (chemical modifications)
Data on an error generated by computer system or tool.
Basic information on any arbitrary database entry.
A molecular sequence and comprehensive metadata (such as a feature table), typically corresponding to a full entry from a molecular sequence database.
An identifier of a plasmid in a database.
A unique identifier of a specific mutation catalogued in a database.
Information describing the mutation itself, the organ site, tissue and type of lesion where the mutation has been identified, description of the patient origin and life-style.
An informative report on the prevalence of mutation(s), including data on samples and mutation prevalence (e.g. by tumour type)..
An informative report on mutation prognostic data, such as information on patient cohort, the study settings and the results of the study.
An informative report on the functional properties of mutant proteins including transcriptional activities, promotion of cell growth and tumorigenicity, dominant negative effects, capacity to induce apoptosis, cell-cycle arrest or checkpoints in human cells and so on.
The number of a codon, for instance, at which a mutation is located.
An informative report on a specific tumor including nature and origin of the sample, anatomic site, organ or tissue, tumor type, including morphology and/or histologic type, and so on.
Basic information about a server on the web, such as an SRS server.
Unique identifier of a sequence cluster from the SYSTERS database.
Raw SCOP domain classification data files.
These are the parsable data files provided by SCOP.
Raw CATH domain classification data files.
These are the parsable data files provided by CATH.
An informative report on the types of small molecules or 'heterogens' (non-protein groups) that are represented in PDB files.
A collection of sequences output from a bootstrapping (resampling) procedure.
Bootstrapping is often performed in phylogenetic analysis.
A consensus phylogenetic tree derived from comparison of multiple trees.
A data schema for organising or transforming data of some type.
Name of an OBO file format such as OBO-XML, plain and so on.
Identifier for genetic elements in MIPS database.
An identifier of protein sequence(s) or protein sequence database entries.
An identifier of nucleotide sequence(s) or nucleotide sequence database entries.
An accession number of an entry from the EMBL sequence database.
An identifier of a polypeptide in the UniProt database.
Accession number of an entry from the GenBank sequence database.
Secondary (internal) identifier of a Gramene database entry.
An identifier of an entry from a database of molecular sequence variation.
A unique (and typically persistent) identifier of a gene in a database, that is (typically) different to the gene name/symbol.
Name of an entry (gene) from the AceView genes database.
http://www.geneontology.org/doc/GO.xrf_abbs: ECK
Identifier of an E. coli K-12 gene from EcoGene Database.
Identifier for a gene approved by the HUGO Gene Nomenclature Committee.
The name of a gene, (typically) assigned by a person and/or according to a naming scheme. It may contain white space characters and is typically more intuitive and readable than a gene symbol. It (typically) may be used to identify similar genes in different species and to derive a gene symbol.
Name of an entry (gene) from the NCBI genes database.
A specification of a chemical structure in SMILES format.
Unique identifier of an entry from the STRING database of protein-protein interactions.
An informative report on a specific virus.
An informative report on the taxonomy of a specific virus.
Identifier of a biological reaction from the SABIO-RK reactions database.
A human-readable collection of information about one or more specific carbohydrate 3D structure(s).
A series of digits that are assigned consecutively to each sequence record processed by NCBI. The GI number bears no resemblance to the Accession number of the sequence record.
Nucleotide sequence GI number is shown in the VERSION field of the database record. Protein sequence GI number is shown in the CDS/db_xref field of a nucleotide database record, and the VERSION field of a protein database record.
An identifier assigned to sequence records processed by NCBI, made of the accession number of the database record followed by a dot and a version number.
Nucleotide sequence version contains two letters followed by six digits, a dot, and a version number (or for older nucleotide sequence records, the format is one letter followed by five digits, a dot, and a version number). Protein sequence version contains three letters followed by five digits, a dot, and a version number.
A unique, persistent identifier of an enzyme.
Identifier of an enzyme from the REBASE enzymes database.
Unique identifier of a drug from the DrugBank database.
A unique identifier assigned to NCBI protein sequence records.
A score derived from the alignment of two sequences, which is then normalised with respect to the scoring system.
Bit scores are normalised with respect to the scoring system and therefore can be used to compare alignment scores from different searches.
Phase for translation of DNA (0, 1 or 2) relative to a fragment of the coding sequence.
Data concerning or describing some core computational resource, as distinct from primary data. This includes metadata on the origin, source, history, ownership or location of some thing.
Any arbitrary identifier of an ontology.
An identifier of a build of a particular genome.
The name of a biological pathway or network.
Identifier of a pathway from the KEGG pathway database.
Identifier of a pathway from the NCI-Nature pathway database.
Identifier of a pathway from the ConsensusPathDB pathway database.
Unique identifier of an entry from the UniRef database.
Unique identifier of an entry from the UniRef100 database.
Unique identifier of an entry from the UniRef90 database.
Unique identifier of an entry from the UniRef50 database.
Data concerning or derived from an ontology.
A human-readable collection of information about a specific RNA family or other group of classified RNA sequences.
Identifier of an RNA family, typically an entry from a RNA sequence classification database.
Stable accession number of an entry (RNA family) from the RFAM database.
A label (text token) describing a type of protein family signature (sequence classifier) from the InterPro database.
An informative report on protein domain-DNA/RNA interaction(s).
An informative report on protein domain-protein domain interaction(s).
Data on indirect protein domain-protein domain interaction(s).
Accession number of a nucleotide or protein sequence database entry.
Data concerning two-dimensional polygel electrophoresis.
two-dimensional gel electrophoresis experiments, gels or spots in a gel.
A persistent, unique identifier of a biological pathway or network (typically a database entry).
Alignment of the (1D representations of) secondary structure of two or more molecules.
Identifier of an object from the ASTD database.
Identifier of an exon from the ASTD database.
Identifier of an intron from the ASTD database.
Identifier of a polyA signal from the ASTD database.
Identifier of a transcription start site from the ASTD database.
An informative report on individual spot(s) from a two-dimensional (2D PAGE) gel.
Unique identifier of a spot from a two-dimensional (protein) gel.
Unique identifier of a spot from a two-dimensional (protein) gel in the SWISS-2DPAGE database.
Unique identifier of a spot from a two-dimensional (protein) gel from a HSC-2DPAGE database.
Data on the interaction of a protein (or protein domain) with specific structural (3D) and/or sequence motifs.
Identifier of a strain of an organism variant, typically a plant, virus or bacterium.
A unique identifier of an item from the CABRI database.
Report of genotype experiment including case control, population, and family studies. These might use array based methods and re-sequencing methods.
Identifier of an entry from a database of genotype experiment metadata.
Identifier of an entry from the EGA database.
Identifier of a protein entry catalogued in the International Protein Index (IPI) database.
Accession number of a protein from the RefSeq database.
Identifier of an entry (promoter) from the EPD database.
Identifier of an entry from the TAIR database.
Identifier of an Arabidopsis thaliana gene from the TAIR database.
Identifier of an entry from the UniSTS database.
Identifier of an entry from the UNITE database.
Identifier of an entry from the UTR database.
Accession number of a UniParc (protein sequence) database entry.
Identifier of an entry from the Rouge or HUGE databases.
An informative report on a specific fungus.
An informative report on a specific fungus anamorph.
Unique identifier for a protein from the Ensembl database.
An informative report on a specific toxin.
An informative report on a membrane protein.
An informative report on tentative or known protein-drug interaction(s).
Data concerning a map of molecular sequence(s).
Data concerning phylogeny, typically of molecular sequences, including reports of information concerning or derived from a phylogenetic tree, or from comparing two or more phylogenetic trees.
Data concerning one or more protein molecules.
Data concerning one or more nucleic acid molecules.
Data concerning, extracted from, or derived from the analysis of a scientific text (or texts) such as a full text article from a scientific journal.
This is a broad data type and is used a placeholder for other, more specific types. It is primarily intended to help navigation of EDAM and would not typically be used for annotation. It includes concepts that are best described as scientific text or closely concerned with or derived from text.
Typically a simple numerical or string value that controls the operation of a tool.
Data concerning a specific type of molecule.
An informative report on a specific molecule.
A human-readable collection of information about a specific organism.
A human-readable collection of information about about how a scientific experiment or analysis was carried out that results in a specific set of data or results used for further analysis or to test a specific hypothesis.
An attribute of a molecular sequence, possibly in reference to some other sequence.
Output from a serial analysis of gene expression (SAGE), massively parallel signature sequencing (MPSS) or sequencing by synthesis (SBS) experiment. In all cases this is a list of short sequence tags and the number of times it is observed.
SAGE, MPSS and SBS experiments are usually performed to study gene expression. The sequence tags are typically subsequently annotated (after a database search) with the mRNA (and therefore gene) the tag was extracted from.
This includes tag to gene assignments (tag mapping) of SAGE, MPSS and SBS data. Typically this is the sequencing-based expression profile annotated with gene identifiers.
Data concerning a mass spectrometry measurement.
Raw data from experimental methods for determining protein structure.
Data concerning an alignment of two or more molecular sequences, structures or derived data.
This is a broad data type and is used a placeholder for other, more specific types. This includes entities derived from sequences and structures such as motifs and profiles.
Single letter amino acid identifier, e.g. G.
Three letter amino acid identifier, e.g. GLY.
Full name of an amino acid, e.g. Glycine.
Unique identifier of a toxin from the ArachnoServer database.
Unique identifier of a monomer from the BindingDB database.
The name of a concept from the GO ontology.
An identifier of a 'biological process' concept from the the Gene Ontology.
An identifier of a 'molecular function' concept from the the Gene Ontology.
The name of a concept for a cellular component from the GO ontology.
An image arising from a Northern Blot experiment.
Unique identifier of a blot from a Northern Blot.
Unique identifier of a blot from a Northern Blot from the BlotBase database.
Raw data on a biological hierarchy, describing the hierarchy proper, hierarchy components and possibly associated annotation.
Identifier of an entry from a database of biological hierarchies.
Identifier of an entry from the Brite database of biological hierarchies.
A type (represented as a string) of cancer.
A unique identifier for an organism used in the BRENDA database.
The name of a taxon using the controlled vocabulary of the UniGene database.
The name of a taxon using the controlled vocabulary of the UTRdb database.
An identifier of a catalogue of biological resources.
The name of a catalogue of biological resources from the CABRI database.
Was deprecated since 1.5, but not correctly (fully) obsoleted until 1.19.
An informative report on the physical, chemical or other information concerning the interaction of two or more molecules (or parts of molecules).
Primary data about a specific biological pathway or network (the nodes and connections within the pathway or network).
Data concerning one or more small molecules.
Data concerning a particular genotype, phenotype or a genotype / phenotype relation.
Image, hybridisation or some other data arising from a study of feature/molecule expression, typically profiling or quantification.
Unique identifier of a chemical compound from the KEGG database.
Name (not necessarily stable) an entry (RNA family) from the RFAM database.
Identifier of a biological reaction from the KEGG reactions database.
Unique identifier of a drug from the KEGG Drug database.
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl database.
An identifier of a disease from the International Classification of Diseases (ICD) database.
Unique identifier of a sequence cluster from the CluSTr database.
Unique identifier of a glycan ligand from the KEGG GLYCAN database (a subset of KEGG LIGAND).
A unique identifier of a family from the transport classification database (TCDB) of membrane transport proteins.
Unique identifier of an entry from the MINT database of protein-protein interactions.
Unique identifier of an entry from the DIP database of protein-protein interactions.
Unique identifier of a protein listed in the UCSD-Nature Signaling Gateway Molecule Pages database.
Identifier of a protein modification catalogued in a database.
Identifier of a protein modification catalogued in the RESID database.
Identifier of an entry from the RGD database.
Identifier of a protein sequence from the TAIR database.
Identifier of a small molecule metabolite from the Human Metabolome Database (HMDB).
Identifier of an entry from the LIPID MAPS database.
Identifier of a peptide from the PeptideAtlas peptide databases.
Identifier of a report of molecular interactions from a database (typically).
A unique identifier of an interaction from the BioGRID database.
Unique identifier of a peptidase enzyme from the MEROPS database.
An identifier of a mobile genetic element.
An identifier of a mobile genetic element from the Aclame database.
Identifier of an entry from the Saccharomyces genome database (SGD).
The International Standard Book Number (ISBN) is for identifying printed books.
Identifier of a metabolite from the 3DMET database.
A unique identifier of an interaction from the MatrixDB database.
A unique identifier for pathways, reactions, complexes and small molecules from the cPath (Pathway Commons) database.
These identifiers are unique within the cPath database, however, they are not stable between releases.
Identifier of an assay from the PubChem database.
Identifier of an entry from the PubChem database.
Identifier of an enzyme reaction mechanism from the MACie database.
Identifier for a gene from the miRBase database.
Identifier for a gene from the Zebrafish information network genome (ZFIN) database.
Identifier of an enzyme-catalysed reaction from the Rhea database.
Identifier of a biological pathway from the Unipathway database.
Identifier of a small molecular from the ChEMBL database.
Unique identifier of an entry from the Ligand-gated ion channel (LGICdb) database.
Identifier of a biological reaction (kinetics entry) from the SABIO-RK reactions database.
Identifier of an entry from the pharmacogenetics and pharmacogenomics knowledge base (PharmGKB).
Identifier of a pathway from the pharmacogenetics and pharmacogenomics knowledge base (PharmGKB).
Identifier of a disease from the pharmacogenetics and pharmacogenomics knowledge base (PharmGKB).
Identifier of a drug from the pharmacogenetics and pharmacogenomics knowledge base (PharmGKB).
Identifier of a drug from the Therapeutic Target Database (TTD).
Identifier of a target protein from the Therapeutic Target Database (TTD).
A unique identifier of a type or group of cells.
A unique identifier of a neuron from the NeuronDB database.
A unique identifier of a neuron from the NeuroMorpho database.
Identifier of a chemical from the ChemIDplus database.
Identifier of a pathway from the Small Molecule Pathway Database (SMPDB).
Identifier of an entry from the BioNumbers database of key numbers and associated data in molecular biology.
Unique identifier of a toxin from the Toxin and Toxin Target Database (T3DB) database.
Identifier of an entry from the GlycomeDB database.
Identifier of an entry from the LipidBank database.
Identifier of a conserved domain from the Conserved Domain Database.
An identifier of an entry from the MMDB database.
Unique identifier of an entry from the iRefIndex database of protein-protein interactions.
Unique identifier of an entry from the ModelDB database.
Identifier of a signaling pathway from the Database of Quantitative Cellular Signaling (DQCS).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database (Homo sapiens division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Bos taurus' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Canis familiaris' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Cavia porcellus' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Ciona intestinalis' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Ciona savignyi' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Danio rerio' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Dasypus novemcinctus' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Echinops telfairi' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Erinaceus europaeus' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Felis catus' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Gallus gallus' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Gasterosteus aculeatus' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Homo sapiens' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Loxodonta africana' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Macaca mulatta' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Monodelphis domestica' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Mus musculus' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Myotis lucifugus' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Ornithorhynchus anatinus' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Oryctolagus cuniculus' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Oryzias latipes' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Otolemur garnettii' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Pan troglodytes' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Rattus norvegicus' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Spermophilus tridecemlineatus' division).
Ensembl ID ('Spermophilus tridecemlineatus')
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Takifugu rubripes' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Tupaia belangeri' division).
Identifier of an entry (exon, gene, transcript or protein) from the Ensembl 'core' database ('Xenopus tropicalis' division).
Identifier of a protein domain (or other node) from the CATH database.
A code number identifying a family from the CATH database.
Identifier of an enzyme from the CAZy enzymes database.
A unique identifier assigned by the I.M.A.G.E. consortium to a clone (cloned molecular sequence).
An identifier of a 'cellular component' concept from the Gene Ontology.
GO concept identifier (cellular compartment)
Name of a chromosome as used in the BioCyc database.
An identifier of a gene expression profile from the CleanEx database.
An identifier of (typically a list of) gene expression experiments catalogued in the CleanEx database.
A human-readable collection of information concerning a genome as a whole.
Unique identifier for a protein complex from the CORUM database.
Unique identifier of a position-specific scoring matrix from the CDD database.
Unique identifier for a protein from the CuticleDB database.
Identifier of a predicted transcription factor from the DBD database.
General annotation on an oligonucleotide probe, or a set of probes.
Identifier of an oligonucleotide from a database.
Identifier of an oligonucleotide probe from the dbProbe database.
Physicochemical property data for one or more dinucleotides.
Identifier of an dinucleotide property from the DiProDB database.
Protein features report (disordered structure)
Unique identifier for a protein from the DisProt database.
Annotation on an embryo or concerning embryological development.
Unique identifier for a gene transcript from the Ensembl database.
An informative report on one or more small molecules that are enzyme inhibitors.
An identifier of a promoter of a gene that is catalogued in a database.
Identifier of an EST sequence from the COGEME database.
Identifier of a unisequence from the COGEME database.
A unisequence is a single sequence assembled from ESTs.
A feature identifier as used in the SwissRegulon database.
This can be name of a gene, the ID of a TFBS, or genomic coordinates in form "chr:start..end".
A unique identifier of gene in the NMPDR database.
A FIG ID consists of four parts: a prefix, genome id, locus type and id number.
A unique identifier of gene in the Xenbase database.
A unique identifier of gene in the Genolist database.
Name of an entry (gene) from the Genolist genes database.
Identifier of an entry (promoter) from the ABS database.
Identifier of a transcription factor from the AraC-XylS database.
Name of an entry (gene) from the HUGO database.
Identifier of a locus from the PseudoCAP database.
Identifier of a locus from the UTR database.
Unique identifier of a monosaccharide from the MonosaccharideDB database.
The name of a subdivision of the Collagen Mutation Database (CMD) database.
The name of a subdivision of the Osteogenesis database.
Identifier of an entry from the GlycosciencesDB database.
A conformational energy map of the glycosidic linkages in a carbohydrate molecule.
Identifier of a membrane transport proteins from the transport classification database (TCDB).
Name of a domain from the Pfam database.
Identifier for a gene from the VectorBase database.
Identifier of an entry from the UTRSite database of regulatory motifs in eukaryotic UTRs.
An informative report about a specific or conserved pattern in a molecular sequence, such as its context in genes or proteins, its role, origin or method of construction, etc.
An informative report on a particular locus.
Official name of a protein as used in the UniProt database.
One or more terms from one or more controlled vocabularies which are annotations on an entity.
The concepts are typically provided as a persistent identifier or some other link the source ontologies. Evidence of the validity of the annotation might be included.
Name of a protein family from the HAMAP database.
Basic information concerning an identifier of data (typically including the identifier itself). For example, a gene symbol with information concerning its provenance.
Identifier of an RNA transcript from the H-InvDB database.
A unique identifier of gene cluster in the H-InvDB database.
Identifier of a antibody from the HPA database.
Identifier of a human major histocompatibility complex (HLA) or other protein from the IMGT/HLA database.
A unique identifier of gene assigned by the J. Craig Venter Institute (JCVI).
Identifier of a physical entity from the ConsensusPathDB database.
Name of a physical entity from the ConsensusPathDB database.
The number of a strain of algae and protozoa from the CCAP database.
An identifier of stock from a catalogue of biological resources.
A stock number from The Arabidopsis information resource (TAIR).
Identifier of an entry from the RNA editing database (REDIdb).
Name of a domain from the SMART database.
Accession number of an entry (family) from the PANTHER database.
A unique identifier for a virus from the RNAVirusDB database.
Could list (or reference) other taxa here from https://www.phenoscape.org/wiki/Taxonomic_Rank_Vocabulary.
An accession of annotation on a (group of) viruses (catalogued in a database).
An identifier of a genome project assigned by NCBI.
A unique identifier of a whole genome assigned by the NCBI.
Data concerning, extracted from, or derived from the analysis of a sequence profile, such as its name, length, technical details about the profile or it's construction, the biological role or annotation, and so on.
Unique identifier for a membrane protein from the TopDB database.
Identifier of a two-dimensional (protein) gel.
Name of a reference map gel from the SWISS-2DPAGE database.
Unique identifier for a peroxidase protein from the PeroxiBase database.
Identifier of an entry from the SISYPHUS database of tertiary structure alignments.
Accession of an open reading frame (catalogued in a database).
Unique identifier for a ligand-gated ion channel protein from the LGICdb database.
Identifier of an EST sequence from the MaizeDB database.
A unique identifier of gene in the MfunGD database.
An identifier of a disease from the Orpha database.
Unique identifier for a protein from the EcID database.
A unique identifier of a cDNA molecule catalogued in the RefSeq database.
Unique identifier for a cone snail toxin protein from the ConoServer database.
A web site providing data (web pages) on a common theme to a HTTP client.
Identifier for a gene from the VBASE2 database.
A unique identifier for a virus from the DPVweb database.
Identifier of a pathway from the BioSystems pathway database.
Data concerning a proteomics experiment.
3D coordinate and associated data for a lipid structure.
3D coordinate and associated data for the (3D) structure of a drug.
3D coordinate and associated data for the (3D) structure of a toxin.
A simple matrix of numbers, where each value (or column of values) is derived derived from analysis of the corresponding position in a sequence alignment.
A matrix of distances between molecular entities, where a value (distance) is (typically) derived from comparison of two entities and reflects their similarity.
Distances (values representing similarity) between a group of molecular structures.
Bibliographic data concerning scientific article(s).
This includes any fields from the concept definition such as concept name, definition, comments and so on.
A numerical measure of differences in the frequency of occurrence of synonymous codons in DNA sequences.
A map showing distance between genetic markers estimated by radiation-induced breaks in a chromosome.
The radiation method can break very closely linked markers providing a more detailed map. Most genetic markers and subsequences may be located to a defined map position and with a more precise estimates of distance than a linkage map.
A simple list of data identifiers (such as database accessions), possibly with additional basic information on the addressed data.
Gene frequencies data that may be read during phylogenetic tree calculation.
A set of sub-sequences displaying some type of polymorphism, typically indicating the sequence in which they occur, their position and other metadata.
An entry (resource) from the DRCAT bioinformatics resource catalogue.
3D coordinate and associated data for a multi-protein complex; two or more polypeptides chains in a stable, functional association with one another.
3D coordinate and associated data for a protein (3D) structural motif; any group of contiguous or non-contiguous amino acid residues but typically those forming a feature with a structural or functional role.
A human-readable collection of information about one or more specific lipid 3D structure(s).
Image of one or more molecular secondary structures.
An informative report on general information, properties or features of one or more molecular secondary structures.
DNA sequence-specific feature annotation (not in a feature table).
Features concerning RNA or regions of DNA that encode an RNA molecule.
Biological data that has been plotted as a graph of some type, or plotting instructions for rendering such a graph.
A protein sequence and associated metadata.
A nucleic acid sequence and associated metadata.
A protein sequence and comprehensive metadata (such as a feature table), typically corresponding to a full entry from a molecular sequence database.
A nucleic acid sequence and comprehensive metadata (such as a feature table), typically corresponding to a full entry from a molecular sequence database.
Accession of a mathematical model, typically an entry from a database.
Accession of a type or group of cells (catalogued in a database).
Accession of an entry from a database of chemicals.
Accession of a toxin (catalogued in a database).
Accession of a monosaccharide (catalogued in a database).
Accession of an entry from a database of carbohydrates.
Accession of a specific molecule (catalogued in a database).
Accession of a data definition (catalogued in a database).
An accession of a particular genome (in a database).
An accession of a map of a molecular sequence (deposited in a database).
Accession of an entry from a database of lipids.
Accession of a peptide deposited in a database.
Accession of a protein deposited in a database.
An accession of annotation on a (group of) organisms (catalogued in a database).
The name of an organism (or group of organisms).
Accession of a protein family (that is deposited in a database).
Accession of an entry from a database of transcription factors or binding sites.
An identifier of an entry from the DDBJ sequence database.
An identifier of an entity from the ConsensusPathDB database.
Data concerning, extracted from, or derived from the analysis of molecular sequence(s).
Data derived from the analysis of a scientific text such as a full text article from a scientific journal.
An informative report of information about molecular sequence(s), including basic information (metadata), and reports generated from molecular sequence analysis, including positional features and non-positional properties.
Data concerning the properties or features of one or more protein secondary structures.
A Hopp and Woods plot of predicted antigenicity of a peptide or protein.
A melting curve of a double-stranded nucleic acid molecule (DNA or DNA/RNA).
A probability profile of a double-stranded nucleic acid molecule (DNA or DNA/RNA).
A temperature profile of a double-stranded nucleic acid molecule (DNA or DNA/RNA).
A report typically including a map (diagram) of a gene regulatory network.
An informative report on a two-dimensional (2D PAGE) gel.
General annotation on a set of oligonucleotide probes, such as the gene name with which the probe set is associated and which probes belong to the set.
An image from a microarray experiment which (typically) allows a visualisation of probe hybridisation and gene-expression data.
Data (typically biological or biomedical) that has been rendered into an image, typically for display on screen.
Image of a molecular sequence, possibly with sequence features or properties shown.
A report on protein properties concerning hydropathy.
Data concerning a computational workflow.
Data concerning molecular secondary structure data.
A raw protein sequence (string of characters).
One or more protein sequences, possibly with associated annotation.
One or more nucleic acid sequences, possibly with associated annotation.
Data concerning a biochemical reaction, typically data and more general annotation on the kinetics of enzyme-catalysed reaction.
An informative report concerning the classification of protein sequences or structures.
Data concerning specific or conserved pattern in molecular sequences.
Data concerning models representing a (typically multiple) sequence alignment.
Data concerning a specific biological pathway or network.
An informative report concerning or derived from the analysis of a biological pathway or network, such as a map (diagram) or annotation.
A thermodynamic or kinetic property of a nucleic acid molecule.
Nucleic acid property (thermodynamic or kinetic)
Data concerning the classification of nucleic acid sequences or structures.
A report on a classification of molecular sequences, structures or other entities.
This can include an entire classification, components such as classifiers, assignments of entities to a classification and so on.
key residues involved in protein folding.
Protein features report (key folding sites)
Geometry data for a protein structure, for example bond lengths, bond angles, torsion angles, chiralities, planaraties etc.
Weights for sequence positions or characters in phylogenetic analysis where zero is defined as unweighted.
Annotation of one particular positional feature on a biomolecular (typically genome) sequence, suitable for import and display in a genome browser.
Accession number of a UniProt (protein sequence) database entry.
Identifier of a genetic code in the NCBI list of genetic codes.
Identifier of a concept in an ontology of biological or bioinformatics concepts and relations.
The name of a concept for a biological process from the GO ontology.
The name of a concept for a molecular function from the GO ontology.
Data concerning the classification, identification and naming of organisms.
EMBL/GENBANK/DDBJ coding feature protein identifier, issued by International collaborators.
This qualifier consists of a stable ID portion (3+5 format with 3 position letters and 5 numbers) plus a version number after the decimal point. When the protein sequence encoded by the CDS changes, only the version number of the /protein_id value is incremented; the stable part of the /protein_id remains unchanged and as a result will permanently be associated with a given protein; this qualifier is valid only on CDS features which translate into a valid protein.
A type of data that (typically) corresponds to entries from the primary biological databases and which is (typically) the primary input or output of a tool, i.e. the data the tool processes or generates, as distinct from metadata and identifiers which describe and identify such core data, parameters that control the behaviour of tools, reports of derivative data generated by tools and annotation.
Core data entities typically have a format and may be identified by an accession number.
Name or other identifier of molecular sequence feature(s).
An identifier of a molecular tertiary structure, typically an entry from a structure database.
An identifier of an array of numerical values, such as a comparison matrix.
A report (typically a table) on character or word composition / frequency of protein sequence(s).
A report (typically a table) on character or word composition / frequency of nucleic acid sequence(s).
Nucleic acid sequence composition (report)
A node from a classification of protein structural domain(s).
Duplicates http://edamontology.org/data_1002, hence deprecated.
Unique numerical identifier of chemicals in the scientific literature, as assigned by the Chemical Abstracts Service.
Unique identifier of a drug conforming to the Anatomical Therapeutic Chemical (ATC) Classification System, a drug classification system controlled by the WHO Collaborating Centre for Drug Statistics Methodology (WHOCC).
A unique, unambiguous, alphanumeric identifier of a chemical substance as catalogued by the Substance Registration System of the Food and Drug Administration (FDA).
Basic information concerning geographical location or time.
Metadata concerning the software, hardware or other aspects of a computer system.
A name of a sequence feature, e.g. the name of a feature to be displayed to an end-user.
Raw data such as measurements or other results from laboratory experiments, as generated from laboratory hardware.
Raw data (typically MIAME-compliant) for hybridisations from a microarray experiment.
Such data as found in Affymetrix CEL or GPR files.
Data generated from processing and analysis of probe set data from a microarray experiment.
Such data as found in Affymetrix .CHP files or data from other software such as RMA or dChip.
The final processed (normalised) data for a set of hybridisations in a microarray experiment.
This combines data from all hybridisations.
Annotation on a biological sample, for example experimental factors and their values.
This might include compound and dose in a dose response experiment.
Annotation on the array itself used in a microarray experiment.
This might include gene identifiers, genomic coordinates, probe oligonucleotide sequences etc.
Annotation on laboratory and/or data processing protocols used in an microarray experiment.
This might describe e.g. the normalisation methods used to process the raw data.
Data concerning the hybridisations measured during a microarray experiment.
A report of regions in a molecular sequence that are biased to certain characters.
Sequence features (compositionally-biased regions)
A report on features in a nucleic acid sequence that indicate changes to or differences between sequences.
Nucleic acid features (difference and change)
The report may be based on analysis of nucleic acid sequence or structural data, or any annotation or information about specific nucleic acid 3D structure(s) or such structures in general.
A human-readable collection of information about regions within a nucleic acid sequence which form secondary or tertiary (3D) structures.
short repetitive subsequences (repeat sequences) in a protein sequence.
Report on the location of matches to profiles, motifs (conserved or functional patterns) or other signatures in one or more protein sequences.
Report on the location of matches to profiles, motifs (conserved or functional patterns) or other signatures in one or more nucleic acid sequences.
A report on displacement loops in a mitochondrial DNA sequence.
A displacement loop is a region of mitochondrial DNA in which one of the strands is displaced by an RNA molecule.
A report on stem loops in a DNA sequence.
A stem loop is a hairpin structure; a double-helical structure formed when two complementary regions of a single strand of RNA or DNA molecule form base-pairs.
An informative report on features of a messenger RNA (mRNA) molecules including precursor RNA, primary (unprocessed) transcript and fully processed molecules. This includes reports on a specific gene transcript, clone or EST.
This includes 5'untranslated region (5'UTR), coding sequences (CDS), exons, intervening sequences (intron) and 3'untranslated regions (3'UTR).
features of non-coding or functional RNA molecules, including tRNA and rRNA.
Features concerning transcription of DNA into RNA including the regulation of transcription.
This includes promoters, CAAT signals, TATA signals, -35 signals, -10 signals, GC signals, primer binding sites for initiation of transcription or reverse transcription, enhancer, attenuator, terminators and ribosome binding sites.
A report on predicted or actual immunoglobulin gene structure including constant, switch and variable regions and diversity, joining and variable segments.
Nucleic acid features (immunoglobulin gene structure)
Information on a 'class' node from the SCOP database.
Information on a 'fold' node from the SCOP database.
Information on a 'superfamily' node from the SCOP database.
Information on a 'family' node from the SCOP database.
Information on a 'protein' node from the SCOP database.
Information on a 'species' node from the SCOP database.
A human-readable collection of information about a particular family of genes, typically a set of genes with similar sequence that originate from duplication of a common ancestor gene, or any other classification of nucleic acid sequences or structures that reflects gene structure.
This includes reports on on gene homologues between species.
An alignment of protein sequences and/or structures.
sequencing experiment, including samples, sampling, preparation, sequencing, and analysis.
An informative report about a DNA sequence assembly.
This might include an overall quality assement of the assembly and summary statistics including counts, average length and number of bases for reads, matches and non-matches, contigs, reads in pairs etc.
Many sequence alignment tasks involving many or very large sequences rely on a precomputed index of the sequence to accelerate the alignment.
Report concerning genome-wide association study experiments.
The position of a cytogenetic band in a genome.
Information might include start and end position in a chromosome sequence, chromosome identifier, name of band and so on.
Mathematical model of a network, that contains biochemical kinetics.
A label (text token) describing a type of sequence feature such as gene, transcript, cds, exon, repeat, simple, misc, variation, somatic variation, structural variation, somatic structural variation, constrained or regulatory.
An informative report on gene homologues between species.
Unique identifier for a gene tree from the Ensembl database.
A phylogenetic tree that is an estimate of the character's phylogeny.
A phylogenetic tree that reflects phylogeny of the taxa from which the characters (used in calculating the tree) were sampled.
Name or other identifier of an entry from a biosample database.
Identifier of an object from the MGI database.
A HMM transition matrix contains the probabilities of switching from one HMM state to another.
Consider for example an HMM with two states (AT-rich and GC-rich). The transition matrix will hold the probabilities of switching from the AT-rich to the GC-rich state, and vica versa.
A HMM emission matrix holds the probabilities of choosing the four nucleotides (A, C, G and T) in each of the states of a HMM.
Consider for example an HMM with two states (AT-rich and GC-rich). The emission matrix holds the probabilities of choosing each of the four nucleotides (A, C, G and T) in the AT-rich state and in the GC-rich state.
A statistical Markov model of a system which is assumed to be a Markov process with unobserved (hidden) states.
Hidden Markov model
Raw biological or biomedical image generated by some experimental technique.
Data concerning the intrinsic physical (e.g. structural) or chemical properties of one, more or all carbohydrates.
Report concerning proteomics experiments.
biological computational model experiments (simulation), for example the minimum information required in order to permit its correct interpretation and reproduction.
An imaging technique that uses magnetic fields and radiowaves to form images, typically to investigate the anatomy and physiology of the human body.
Nuclear magnetic resonance imaging image
An image from a cell migration track assay.
Rate of association of a protein with another protein or some other molecule.
Multiple gene identifiers in a specific order.
Such data are often used for genome rearrangement tools and phylogenetic tree labeling.
The spectrum of frequencies of electromagnetic radiation emitted from a molecule as a result of some spectroscopy experiment.
Spectral information for a molecule from a nuclear magnetic resonance experiment.
A sketch of a small molecule made with some specialised drawing package.
Chemical structure sketches are used for presentational purposes but also as inputs to various analysis software.
An informative report about a specific or conserved nucleic acid sequence pattern.
Data on gene sequence variations resulting large-scale genotyping and DNA sequencing projects.
Variations are stored along with a reference genome.
A list of publications such as scientic papers or books.
A mapping of supplied textual terms or phrases to ontology concepts (URIs).
Any data concerning a specific biological or biomedical image.
This can include basic provenance and technical information about the image, scientific annotation and so on.
A human-readable collection of information concerning a clinical trial.
Accession number of an entry from the Gene Expression Atlas.
Identifier of an entry from a database of disease.
Some material that is used for educational (training) purposes.
A training course available for use on the Web.
Any free or plain text, typically for human consumption and in English. Can instantiate also as a textual search query.
A human-readable collection of information concerning biosafety data.
A report about any kind of isolation of biological material.
Information about the ability of an organism to cause disease in a corresponding host.
Information about the biosafety classification of an organism according to corresponding law.
A report about localisation of the isolaton of biological material e.g. country or coordinates.
A report about any kind of isolation source of biological material e.g. blood, water, soil.
Experimentally determined parameter of the physiology of an organism, e.g. substrate spectrum.
Experimentally determined parameter of the morphology of an organism, e.g. size & shape.
Experimental determined parameter for the cultivation of an organism.
Data concerning a sequencing experiment, that may be specified as an input to some tool.
An identifier of a flow cell of a sequencing machine.
A flow cell is used to immobilise, amplify and sequence millions of molecules at once. In Illumina machines, a flowcell is composed of 8 "lanes" which allows 8 experiments in a single analysis.
An identifier of a lane within a flow cell of a sequencing machine, within which millions of sequences are immobilised, amplified and sequenced.
A number corresponding to the number of an analysis performed by a sequencing machine. For example, if it's the 13th analysis, the run is 13.
Data concerning ecology; for example measurements and reports from the study of interactions among organisms and their environment.
The mean species diversity in sites or habitats at a local scale.
The ratio between regional and local species diversity.
The total species diversity in a landscape.
A plot in which community data (e.g. species abundance data) is summarised. Similar species and samples are plotted close together, and dissimilar species and samples are plotted placed far apart.
A ranked list of categories (usually ontology concepts), each associated with a statistical metric of over-/under-representation within the studied data.
A ranked list of Gene Ontology concepts, each associated with a p-value, concerning or derived from the analysis of e.g. a set of genes or proteins.
Gene ontology concept over-representation report
Score for localization of one or more post-translational modifications in peptide sequence measured by mass spectrometry.
Identifier of a protein modification catalogued in the Unimod database.
Identifier for mass spectrometry proteomics data in the proteomexchange.org repository.
Groupings of expression profiles according to a clustering algorithm.
An identifier of a concept from the BRENDA ontology.
A text (such as a scientific article), annotated with notes, data and metadata, such as recognised entities, concepts, and their relations.
A structured query, in form of a script, that defines a database search task.
Structural 3D model (volume map) from electron microscopy.
Annotation on a structural 3D EM Map from electron microscopy. This might include one or several locations in the map of the known features of a particular macromolecule.
Raw DDD movie acquisition from electron microscopy.
Raw acquistion from electron microscopy or average of an aligned DDD movie.
Data coming from molecular simulations, computer "experiments" on model molecules.
Typically formed by two separated but indivisible pieces of information: topology data (static) and trajectory data (dynamic).
Identifier of an entry from the RNA central database of annotated human miRNAs.
There are canonical and taxon-specific forms of RNAcentral ID. Canonical form e.g. urs_9or10digits identifies an RNA sequence (within the RNA central database) which may appear in multiple sequences. Taxon-specific form identifies a sequence in the specific taxon (e.g. urs_9or10digits_taxonID).
A human-readable systematic collection of patient (or population) health information in a digital format.
Data coming from molecular simulations, computer "experiments" on model molecules. Tipically formed by two separated but indivisible pieces of information: topology data (static) and trajectory data (dynamic).
Dynamic information of a structure molecular system coming from a molecular simulation: XYZ 3D coordinates (sometimes with their associated velocities) for every atom along time.
Force field parameters: charges, masses, radii, bond lengths, bond dihedrals, etc. define the structural molecular system, and are essential for the proper description and simulation of a molecular system.
Static information of a structure molecular system that is needed for a molecular simulation: the list of atoms, their non-bonded parameters for Van der Waals and electrostatic interactions, and the complete connectivity in terms of bonds, angles and dihedrals.
Visualization of distribution of quantitative data, e.g. expression data, by histograms, violin plots and density plots.
A table of unnormalized values representing summarised read counts per genomic region (e.g. gene, transcript, peak).
Alignment (superimposition) of DNA tertiary (3D) structures.
A score derived from the P-value to ensure correction for multiple tests. The Q-value provides an estimate of the positive False Discovery Rate (pFDR), i.e. the rate of false positives among all the cases reported positive: pFDR = FP / (FP + TP).
Q-values are widely used in high-throughput data analysis (e.g. detection of differentially expressed genes from transcriptome data).
A profile HMM is a variant of a Hidden Markov model that is derived specifically from a set of (aligned) biological sequences. Profile HMMs provide the basis for a position-specific scoring system, which can be used to align sequences and search databases for related sequences.
Identifier of a pathway from the WikiPathways pathway database.
A ranked list of pathways, each associated with z-score, p-value or similar, concerning or derived from the analysis of e.g. a set of genes or proteins.
Chemical structure specified in Simplified Molecular Input Line Entry System (SMILES) line notation.
Chemical structure specified in IUPAC International Chemical Identifier (InChI) line notation.
Chemical structure specified by Molecular Formula (MF), including a count of each element in a compound.
The general MF query format consists of a series of valid atomic symbols, with an optional number or range.
The InChIKey (hashed InChI) is a fixed length (25 character) condensed digital representation of an InChI chemical structure specification. It uniquely identifies a chemical compound.
An InChIKey identifier is not human- nor machine-readable but is more suitable for web searches than an InChI chemical structure specification.
SMILES ARbitrary Target Specification (SMARTS) format for chemical structure specification, which is a subset of the SMILES line notation.
Alphabet for a molecular sequence with possible unknown positions but without ambiguity or non-sequence characters.
Alphabet for a nucleotide sequence with possible ambiguity, unknown positions and non-sequence characters.
Non-sequence characters may be used for example for gaps.
Alphabet for a protein sequence with possible ambiguity, unknown positions and non-sequence characters.
Non-sequence characters may be used for gaps and translation stop.
Alphabet for the consensus of two or more molecular sequences.
Alphabet for a nucleotide sequence with possible ambiguity and unknown positions but without non-sequence characters.
Alphabet for a nucleotide sequence (characters ACGTU only) with possible unknown positions but without ambiguity or non-sequence characters .
Alphabet for a DNA sequence with possible ambiguity, unknown positions and non-sequence characters.
Alphabet for an RNA sequence with possible ambiguity, unknown positions and non-sequence characters.
Alphabet for a DNA sequence (characters ACGT only) with possible unknown positions but without ambiguity or non-sequence characters.
Alphabet for a DNA sequence with possible ambiguity and unknown positions but without non-sequence characters.
Alphabet for an RNA sequence (characters ACGU only) with possible unknown positions but without ambiguity or non-sequence characters.
Alphabet for an RNA sequence with possible ambiguity and unknown positions but without non-sequence characters.
Alphabet for any protein sequence with possible unknown positions but without ambiguity or non-sequence characters.
Alphabet for any protein sequence with possible ambiguity and unknown positions but without non-sequence characters.
A UniGene entry includes a set of transcript sequences assigned to the same transcription locus (gene or expressed pseudogene), with information on protein similarities, gene expression, cDNA clone reagents, and genomic location.
Format of an entry from the COG database of clusters of (related) protein sequences.
Format for sequence positions (feature location) as used in DDBJ/EMBL/GenBank database.
Report format for tandem repeats in a nucleotide sequence (format generated by the Sanger Centre quicktandem program).
Report format for inverted repeats in a nucleotide sequence (format generated by the Sanger Centre inverted program).
Report format for tandem repeats in a sequence (an EMBOSS report format).
Format of a report on exon-intron structure generated by EMBOSS est2genome.
Report format for restriction enzyme recognition sites used by EMBOSS restrict program.
Report format for restriction enzyme recognition sites used by EMBOSS restover program.
Report format for restriction enzyme recognition sites used by REBASE database.
Format of results of a sequence database search using FASTA.
This includes (typically) score data, alignment data and a histogram (of observed and expected distribution of E values.)
Format of results of a sequence database search using some variant of BLAST.
This includes score data, alignment data and summary table.
Format of results of a sequence database search using some variant of MSPCrunch.
Format of results of a sequence database search using some variant of Smith Waterman.
Format of EMBASSY domain hits file (DHF) of hits (sequences) with domain classification information.
The hits are relatives to a SCOP or CATH family and are found from a search of a sequence database.
Format of EMBASSY ligand hits file (LHF) of database hits (sequences) with ligand classification information.
The hits are putative ligand-binding sequences and are found from a search of a sequence database.
Results format for searches of the InterPro database.
Format of results of a search of the InterPro database showing matches of query protein sequence(s) to InterPro entries.
The report includes a classification of regions in a query protein sequence which are assigned to a known InterPro protein family or group.
Format of results of a search of the InterPro database showing matches between protein sequence(s) and signatures for an InterPro entry.
The table presents matches between query proteins (rows) and signature methods (columns) for this entry. Alternatively the sequence(s) might be from from the InterPro entry itself. The match position in the protein sequence and match status (true positive, false positive etc) are indicated.
Format of a report from the HMMER package on the emission and transition counts of a hidden Markov model.
Format of a regular expression pattern from the Prosite database.
A motif in the format generated by the MEME program.
Sequence profile (sequence classifier) format used in the PROSITE database.
A profile (sequence classifier) in the format used in the JASPAR database.
Format of the model of random sequences used by MEME.
Format of a hidden Markov model representation used by the HMMER package.
FASTA-style format for multiple sequences aligned by HMMER package to an HMM.
Format of multiple sequences aligned by DIALIGN package.
EMBASSY 'domain alignment file' (DAF) format, containing a sequence alignment of protein domains belonging to the same SCOP or CATH family.
The format is clustal-like and includes annotation of domain family classification information.
Format for alignment of molecular sequences to MEME profiles (position-dependent scoring matrices) as generated by the MAST tool from the MEME package.
Format used by the HMMER package for an alignment of a sequence against a hidden Markov model database.
HMMER profile alignment (sequences versus HMMs)
Format used by the HMMER package for of an alignment of a hidden Markov model against a sequence database.
HMMER profile alignment (HMM versus sequences)
Format of PHYLIP phylogenetic distance matrix data.
Data Type must include the distance matrix, probably as pairs of sequence identifiers with a distance (integer or float).
Dendrogram (tree file) format generated by ClustalW.
Raw data file format used by Phylip from which a phylogenetic tree is directly generated or plotted.
PHYLIP file format for continuous quantitative character data.
Phylip continuous quantitative characters
PHYLIP file format for phylogenetics character frequency data.
Phylogenetic tree data format used by the PHYLIP program.
The format of an entry from the TreeBASE database of phylogenetic data.
The format of an entry from the TreeFam database of phylogenetic data.
Format for distances, such as Branch Score distance, between two or more phylogenetic trees as used by the Phylip package.
Format of an entry from the DSSP database (Dictionary of Secondary Structure in Proteins).
The DSSP database is built using the DSSP application which defines secondary structure, geometrical features and solvent exposure of proteins, given atomic coordinates in PDB format.
Entry format of the HSSP database (Homology-derived Secondary Structure in Proteins).
Format of RNA secondary structure in dot-bracket notation, originally generated by the Vienna RNA package/server.
Format of local RNA secondary structure components with free energy values, generated by the Vienna RNA package/server.
Vienna local RNA secondary structure format
Format of an entry (or part of an entry) from the PDB database.
Entry format of PDB database in PDB format.
Entry format of PDB database in mmCIF format.
Entry format of PDB database in PDBML (XML) format.
Format of a matrix of 3D-1D scores used by the EMBOSS Domainatrix applications.
Amino acid index format used by the AAindex database.
Format of an entry from IntEnz (The Integrated Relational Enzyme Database).
IntEnz is the master copy of the Enzyme Nomenclature, the recommendations of the NC-IUBMB on the Nomenclature and Classification of Enzyme-Catalysed Reactions.
Format of an entry from the BRENDA enzyme database.
Format of an entry from the KEGG REACTION database of biochemical reactions.
Format of an entry from the KEGG ENZYME database.
Format of an entry from the proto section of the REBASE enzyme database.
Format of an entry from the withrefm section of the REBASE enzyme database.
Format of output of the Pcons Model Quality Assessment Program (MQAP).
Pcons ranks protein models by assessing their quality based on the occurrence of recurring common three-dimensional structural patterns. Pcons returns a score reflecting the overall global quality and a score for each individual residue in the protein reflecting the local residue quality.
Format of output of the ProQ protein model quality predictor.
ProQ is a neural network-based predictor that predicts the quality of a protein model based on the number of structural features.
The SMART output file includes data on genetically mobile domains / analysis of domain architectures, including phyletic distributions, functional class, tertiary structures and functionally important residues.
Entry format for the BIND database of protein interaction.
Entry format for the IntAct database of protein interaction.
Entry format for the InterPro database of protein signatures (sequence classifiers) and classified sequences.
This includes signature metadata, sequence references and a reference to the signature itself. There is normally a header (entry accession numbers and name), abstract, taxonomy information, example proteins etc. Each entry also includes a match list which give a number of different views of the signature matches for the sequences in each InterPro entry.
Entry format for the textual abstract of signatures in an InterPro entry and its protein matches.
References are included and a functional inference is made where possible.
Entry format for the Gene3D protein secondary database.
Entry format for the PIRSF protein secondary database.
Entry format for the PRINTS protein secondary database.
Entry format for the Panther library of protein families and subfamilies.
Entry format for the Pfam protein secondary database.
Entry format for the SMART protein secondary database.
Entry format for the Superfamily protein secondary database.
Entry format for the TIGRFam protein secondary database.
Entry format for the ProDom protein domain classification database.
A report format for the kinetics of enzyme-catalysed reaction(s) in a format generated by EMBOSS findkm. This includes Michaelis Menten plot, Hanes Woolf plot, Michaelis Menten constant (Km) and maximum velocity (Vmax).
Entry format of Ensembl genome database.
Entry format of DictyBase genome database.
Entry format of Candida Genome database.
Entry format of DragonDB genome database.
Entry format of FlyBase genome database.
Entry format of Gramene genome database.
Entry format of KEGG GENES genome database.
Entry format of the Maize genetics and genomics database (MaizeGDB).
Entry format of the Mouse Genome Database (MGD).
Entry format of the Rat Genome Database (RGD).
Entry format of the Saccharomyces Genome Database (SGD).
Entry format of the Sanger GeneDB genome database.
Entry format of The Arabidopsis Information Resource (TAIR) genome database.
Entry format of the WormBase genomes database.
Entry format of the Zebrafish Information Network (ZFIN) genome database.
Entry format of the TIGR genome database.
Format of an entry from the OMIM database of genotypes and phenotypes.
Format of a record from the HGVbase database of genotypes and phenotypes.
Format of a record from the HIVDB database of genotypes and phenotypes.
Format of an entry from the KEGG DISEASE database.
Report format on PCR primers and hybridisation oligos as generated by Whitehead primer3 program.
A format of raw sequence read data from an Applied Biosystems sequencing machine.
Format of MIRA sequence trace information file.
Common Assembly Format (CAF). A sequence assembly format including contigs, base-call qualities, and other metadata.
Sequence assembly project file EXP format.
Staden Chromatogram Files format (SCF) of base-called sequence reads, qualities, and other metadata.
PHD sequence trace format to store serialised chromatogram data (reads).
Format of Affymetrix data file of raw image data.
Format of Affymetrix data file of information about (raw) expression levels of the individual probes.
Format of affymetrix gene cluster files (hc-genes.txt, hc-chips.txt) from hierarchical clustering.
Entry format for the ArrayExpress microarrays database.
Affymetrix data file format for information about experimental conditions and protocols.
Affymetrix experimental conditions data file format
Format of Affymetrix data file of information about (normalised) expression levels of the individual probes.
Format of an entry from the Electron Microscopy DataBase (EMDB).
The format of an entry from the KEGG PATHWAY database of pathway maps for molecular interactions and reaction networks.
The format of an entry from the MetaCyc metabolic pathways database.
The format of a report from the HumanCyc metabolic pathways database.
The format of an entry from the INOH signal transduction pathways database.
The format of an entry from the PATIKA biological pathways database.
The format of an entry from the reactome biological pathways database.
The format of an entry from the aMAZE biological pathways and molecular interactions database.
The format of an entry from the CPDB database.
The format of an entry from the Panther Pathways database.
Format of mathematical models from the BioModel database.
Models are annotated and linked to relevant data resources, such as publications, databases of compounds and pathways, controlled vocabularies, etc.
The format of an entry from the KEGG LIGAND chemical database.
The format of an entry from the KEGG COMPOUND database.
The format of an entry from the KEGG PLANT database.
The format of an entry from the KEGG GLYCAN database.
The format of an entry from a database of chemical structures and property predictions.
The format of an entry from Chemical Entities of Biological Interest (ChEBI).
ChEBI includes an ontological classification defining relations between entities or classes of entities.
The format of an entry from the MSDchem ligand dictionary.
The format of an entry from the HET group dictionary (HET groups from PDB files).
The format of an entry from the KEGG DRUG database.
Format of bibliographic reference as used by the PubMed database.
Format for abstracts of scientific articles from the Medline database.
Bibliographic reference information including citation information is included
CiteXplore 'core' citation format including title, journal, authors and abstract.
CiteXplore 'all' citation format includes all known details such as Mesh terms and cross-references.
Article format of the PubMed Central database.
The format of iHOP (Information Hyperlinked over Proteins) text-mining result.
OSCAR format of annotated chemical text.
OSCAR (Open-Source Chemistry Analysis Routines) software performs chemistry-specific parsing of chemical documents. It attempts to identify chemical names, ontology concepts, and chemical data from a document.
Format of an ATOM record (describing data for an individual atom) from a PDB file.
Format of CATH domain classification information for a polypeptide chain.
The report (for example http://www.cathdb.info/chain/1cukA) includes chain identifiers, domain identifiers and CATH codes for domains in a given protein chain.
Format of CATH domain classification information for a protein PDB file.
The report (for example http://www.cathdb.info/pdb/1cuk) includes chain identifiers, domain identifiers and CATH codes for domains in a given PDB file.
Entry (gene) format of the NCBI database.
Report format for biological functions associated with a gene name and its alternative names (synonyms, homonyms), as generated by the GeneIlluminator service.
This includes a gene name and abbreviation of the name which may be in a name space indicating the gene status and relevant organisation.
Format of a report on the DNA and protein sequences for a given gene label from a bacterial chromosome maps from the BacMap database.
Format of a report on Escherichia coli genes, proteins and molecules from the CyberCell Database (CCDB).
Map of a plasmid (circular DNA) in PlasMapper TextMap format.
Phylogenetic tree TreeCon (text) format.
A defined way or layout of representing and structuring data in a computer file, blob, string, message, or elsewhere.
The main focus in EDAM lies on formats as means of structuring data exchanged between different tools or resources. The serialisation, compression, or encoding of concrete data formats/models is not in scope of EDAM. Format 'is format of' Data.
A defined data format has its implicit or explicit data model, and EDAM does not distinguish the two. Some data models however do not have any standard way of serialisation into an exchange format, and those are thus not considered formats in EDAM. (Remark: even broader - or closely related - term to 'Data model' would be an 'Information model'.)
File format denotes only formats of a computer file, but the same formats apply also to data blobs or exchanged messages.
Data format for a molecular sequence record.
Data format for molecular sequence feature information.
Data format for molecular sequence alignment information.
Fasta format variant with database name before ID.
FASTQ short read format ignoring quality scores.
FASTQ short read format with phred quality.
FASTQ Solexa/Illumina 1.0 short read format.
GCG SSF (single sequence file) file format.
GFF feature file format with sequence in the header.
FASTA sequence format including NCBI-style GIs.
Intelligenetics sequence format (strict version).
Jackknifer interleaved and non-interleaved sequence format.
Mega interleaved and non-interleaved sequence format.
GCG MSF (multiple sequence file) file format.
PDB nucleotide sequence format (ATOM lines).
PDB nucleotide sequence format (SEQRES lines).
Plain old FASTA sequence format (unspecified format for IDs).
Raw sequence format with no non-sequence characters.
Stockholm multiple sequence alignment format (used by Pfam and Rfam).
Plain text sequence format (essentially unformatted).
DAS sequence (XML) format (nucleotide-only).
EMBOSS debugging trace sequence format of full internal data content.
Jackknifer output sequence non-interleaved format.
Mega non-interleaved output sequence format.
NCBI FASTA sequence format with NCBI-style IDs.
Nexus/paup non-interleaved sequence format.
General Feature Format (GFF) of sequence features.
Generic Feature Format version 3 (GFF3) of sequence features.
EMBOSS debugging trace feature format of full internal data content.
ClustalW format for (aligned) sequences.
EMBOSS alignment format for debugging trace of full internal data content.
Alignment format for start and end of matches between sequence pairs.
Mega format for (typically aligned) sequences.
Mega non-interleaved format for (typically aligned) sequences.
Nexus/paup format for (aligned) sequences.
Nexus/paup non-interleaved format for (aligned) sequences.
EMBOSS simple sequence pair alignment format.
Phylip non-interleaved format for (aligned) sequences.
Alignment format for score values for pairs of sequences.
EMBOSS simple multiple alignment format.
Simple multiple sequence (alignment) format for SRS.
Simple sequence pair (alignment) format for SRS.
Data format for a biological pathway or network.
Data format for a sequence-profile alignment.
Data format for a sequence-HMM profile alignment.
Data format for a full-text scientific article.
Data format of a report from text mining.
Data format for reports on enzyme kinetics.
Format of a report on a chemical compound.
Format of a report on a particular locus, gene, gene system or groups of genes.
Data format for a molecular tertiary structure.
Format of raw (unplotted) phylogenetic data.
Format of phylogenetic continuous quantitative character data.
Phylogenetic continuous quantitative character format
Format of phylogenetic discrete states data.
Phylogenetic tree report (cliques) format
Phylogenetic tree report (invariants) format
Annotation format for electron microscopy models.
Format for phylogenetic tree distance data.
Phylogenetic tree report (tree distances) format
Format for information about a microarray experimental per se (not the data generated from that experiment).
Format for sequence trace data (i.e. including base call information).
Format of a file of gene expression data, e.g. a gene expression matrix or profile.
Format of a report on genotype / phenotype information.
Genotype and phenotype annotation format
Format of a map of (typically one) molecular sequence annotated with features.
Format of a report on PCR primers or hybridisation oligos in a nucleic acid sequence.
Format of a report of general information about a specific protein.
Format of a report of general information about a specific enzyme.
Format of a matrix of 3D-1D scores (amino acid environment probabilities).
Format of a report on the quality of a protein three-dimensional model.
Protein structure report (quality evaluation) format
Format of a report on sequence hits and associated data from searching a sequence database.
Format of a matrix of genetic distances between molecular sequences.
Data format of a dirichlet distribution.
Data format for the emission and transition counts of a hidden Markov model.
HMM emission and transition counts format
Format for secondary structure (predicted or real) of an RNA molecule.
Format for secondary structure (predicted or real) of a protein molecule.
Format used to specify range(s) of sequence positions.
Alphabet for molecular sequence with possible unknown positions but without non-sequence characters.
Alphabet for a molecular sequence with possible unknown positions but possibly with non-sequence characters.
Alphabet for a molecular sequence with possible unknown positions but without ambiguity characters.
Alphabet for a molecular sequence with possible unknown positions and possible ambiguity characters.
Format used for map of repeats in molecular (typically nucleotide) sequences.
Format used for report on restriction enzyme recognition sites in nucleotide sequences.
Nucleic acid features (restriction sites) format
Format used for report on coding regions in nucleotide sequences.
Format used for clusters of molecular sequences.
Format used for clusters of protein sequences.
Format used for clusters of nucleotide sequences.
A text format resembling EMBL entry format.
This concept may be used for the many non-standard EMBL-like text formats.
A text format resembling FASTQ short read format.
This concept may be used for non-standard FASTQ short read-like formats.
A text sequence format resembling uniprotkb entry format.
Abstract format used by MedLine database.
A serialisation format conforming to the Open Biomedical Ontologies (OBO) model.
A serialisation format conforming to the Web Ontology Language (OWL) model.
This concept may also be used for the many non-standard FASTA-like formats.
Data format for a molecular sequence record, typically corresponding to a full entry from a molecular sequence database.
Data format for a molecular sequence record 'lite', typically molecular sequence and minimal metadata, such as an identifier of the sequence and/or a comment.
This is a placeholder for other more specific concepts. It should not normally be used for annotation.
A text format resembling GenBank entry (plain text) format.
This concept may be used for the non-standard GenBank-like text formats.
Text format for a sequence feature table.
Format of a report on organism strain data / cell line.
Format for a report of strain data as used for CIP database entries.
PHYLIP file format for phylogenetic property data.
Entry format (HTML) for the STRING database of protein interaction.
Entry format (XML) for the STRING database of protein interaction.
GFF feature format (of indeterminate version).
Gene Transfer Format (GTF), a restricted version of GFF.
EMBL entry format wrapped in HTML elements.
Format of an entry from the BioCyc enzyme database.
Format of an entry from the Enzyme nomenclature database (ENZYME).
Format of a report on a gene from the PseudoCAP database.
Format of a report on a gene from the GeneCards database.
Data in text format can be compressed into binary format, or can be a value of an XML element or attribute. Markup formats are not considered textual (or more precisely, not plain-textual).
eXtensible Markup Language (XML) format.
Data in XML format can be serialised into text, or binary format.
Only specific native binary formats are listed under 'Binary format' in EDAM. Generic binary formats - such as any data being zipped, or any XML data being serialised into the Efficient XML Interchange (EXI) format - are not modelled in EDAM. Refer to http://wsio.org/compression_004.
Typical textual representation of a URI.
The format of an entry from the NCI-Nature pathways database.
A placeholder concept for visual navigation by dividing data formats by the content of the data that is represented.
This concept exists only to assist EDAM maintenance and navigation in graphical browsers. It does not add semantic information. The concept branch under 'Format (typed)' provides an alternative organisation of the concepts nested under the other top-level branches ('Binary', 'HTML', 'RDF', 'Text' and 'XML'. All concepts under here are already included under those branches.
Any ontology allowed, none mandatory. Preferrably with URIs but URIs are not mandatory. Non-ontology terms are also allowed as the last resort in case of a lack of suitable ontology.
'BioXSD' belongs to the 'BioXSD|GTrack' ecosystem of generic formats. 'BioXSD in XML' is the XML format based on the common, unified 'BioXSD data model', a.k.a. 'BioXSD|BioJSON|BioYAML'.
BioXSD-schema-based XML format of sequence-based data and some other common data - sequence records, alignments, feature records, references to resources, and more - optimised for integrative bioinformatics, Web services, and object-oriented programming.
A serialisation format conforming to the Resource Description Framework (RDF) model.
Genbank entry format wrapped in HTML elements.
Format of a report on protein features (domain composition).
A format resembling EMBL entry (plain text) format.
This concept may be used for the many non-standard EMBL-like formats.
A format resembling FASTQ short read format.
This concept may be used for the many non-standard FASTA-like formats.
A sequence format resembling uniprotkb entry format.
XML format for a sequence feature table.
Text format for molecular sequence alignment information.
XML format for molecular sequence alignment information.
An XML format resembling EMBL entry format.
This concept may be used for the any non-standard EMBL-like XML formats.
A format resembling GenBank entry (plain text) format.
This concept may be used for the non-standard GenBank-like formats.
Entry format for the STRING database of protein interaction.
Text format (representation) of amino acid residues.
Alphabet for a molecular sequence without any unknown positions or ambiguity characters.
Alphabet for a molecular sequence without unknown positions, ambiguity or non-sequence characters.
Alphabet for a nucleotide sequence (characters ACGTU only) without unknown positions, ambiguity or non-sequence characters .
Alphabet for a DNA sequence (characters ACGT only) without unknown positions, ambiguity or non-sequence characters.
Alphabet for an RNA sequence (characters ACGU only) without unknown positions, ambiguity or non-sequence characters.
completely unambiguous pure rna sequence
Format of a raw molecular sequence (i.e. the alphabet used).
BAM format, the binary, BGZF-formatted compressed version of SAM format for alignment of nucleotide sequences (e.g. sequencing reads) to (a) reference sequence(s). May contain base-call and alignment qualities and other data.
Sequence Alignment/Map (SAM) format for alignment of nucleotide sequences (e.g. sequencing reads) to (a) reference sequence(s). May contain base-call and alignment qualities and other data.
The format supports short and long reads (up to 128Mbp) produced by different sequencing platforms and is used to hold mapped data within the GATK and across the Broad Institute, the Sanger Centre, and throughout the 1000 Genomes project.
Systems Biology Markup Language (SBML), the standard XML format for models of biological processes such as for example metabolism, cell signaling, and gene regulation.
Alphabet for any protein sequence without unknown positions, ambiguity or non-sequence characters.
Data format for molecular sequence alignment information that can hold sequence alignment(s) of only 2 sequences.
Format of sequence variation annotation.
Some variant of Pearson MARKX alignment format.
Some variant of Mega format for (typically aligned) sequences.
Some variant of Phylip format for (aligned) sequences.
AB1 binary format of raw DNA sequence reads (output of Applied Biosystems' sequencing analysis software). Contains an electropherogram and the DNA base sequence.
AB1 uses the generic binary Applied Biosystems, Inc. Format (ABIF).
ACE sequence assembly format including contigs, base-call qualities, and other metadata (version Aug 1998 and onwards).
Browser Extensible Data (BED) format of sequence annotation track, typically to be displayed in a genome browser.
BED detail format includes 2 additional columns (http://genome.ucsc.edu/FAQ/FAQformat#format1.7) and BED 15 includes 3 additional columns for experiment scores (http://genomewiki.ucsc.edu/index.php/Microarray_track).
bigBed format for large sequence annotation tracks, similar to textual BED format.
Wiggle format (WIG) of a sequence annotation track that consists of a value for each sequence position. Typically to be displayed in a genome browser.
bigWig format for large sequence annotation tracks that consist of a value for each sequence position. Similar to textual WIG format.
PSL format of alignments, typically generated by BLAT or psLayout. Can be displayed in a genome browser like a sequence annotation track.
Multiple Alignment Format (MAF) supporting alignments of whole genomes with rearrangements, directions, multiple pieces to the alignment, and so forth.
Typically generated by Multiz and TBA aligners; can be displayed in a genome browser like a sequence annotation track. This should not be confused with MIRA Assembly Format or Mutation Annotation Format.
2bit binary format of nucleotide sequences using 2 bits per nucleotide. In addition encodes unknown nucleotides and lower-case 'masking'.
.nib (nibble) binary format of a nucleotide sequence using 4 bits per nucleotide (including unknown) and its lower-case 'masking'.
genePred table format for gene prediction tracks.
genePred format has 3 main variations (http://genome.ucsc.edu/FAQ/FAQformat#format9 http://www.broadinstitute.org/software/igv/genePred). They reflect UCSC Browser DB tables.
Personal Genome SNP (pgSnp) format for sequence variation tracks (indels and polymorphisms), supported by the UCSC Genome Browser.
axt format of alignments, typically produced from BLASTZ.
LAV format of alignments generated by BLASTZ and LASTZ.
Pileup format of alignment of sequences (e.g. sequencing reads) to (a) reference sequence(s). Contains aligned bases per base of the reference sequence(s).
Variant Call Format (VCF) for sequence variation (indels, polymorphisms, structural variation).
Sequence Read Format (SRF) of sequence trace data. Supports submission to the NCBI Short Read Archive.
ZTR format for storing chromatogram data from DNA sequencing instruments.
Genome Variation Format (GVF). A GFF3-compatible format with defined header and attribute tags for sequence variation.
BCF, the binary version of Variant Call Format (VCF) for sequence variation (indels, polymorphisms, structural variation).
Format of a matrix (array) of numerical values.
Format of data concerning the classification of the sequences and/or structures of protein structural domain(s).
Format of raw SCOP domain classification data files.
Format of raw CATH domain classification data files.
Format of summary of domain classification information for a CATH domain.
Systems Biology Result Markup Language (SBRML), the standard XML format for simulated or calculated results (e.g. trajectories) of systems biology models.
BioPAX is an exchange format for pathway data, with its data model defined in OWL.
EBI Application Result XML is a format returned by sequence similarity search Web services at EBI.
XML Molecular Interaction Format (MIF), standardised by HUPO PSI MI.
phyloXML is a standardised XML format for phylogenetic trees, networks, and associated data.
NeXML is a standardised XML format for rich phyloinformatic data.
MAGE-ML XML format for microarray expression data, standardised by MGED (now FGED).
MAGE-TAB textual format for microarray expression data, standardised by MGED (now FGED).
GCDML XML format for genome and metagenome metadata according to MIGS/MIMS/MIMARKS information standards, standardised by the Genomic Standards Consortium (GSC).
'GTrack' belongs to the 'BioXSD|GTrack' ecosystem of generic formats, and particular to its subset, the 'GTrack ecosystem' (GTrack, GSuite, BTrack). 'GTrack' is the tabular format for representing features of sequences and genomes.
GTrack is a generic and optimised tabular format for genome or sequence feature tracks. GTrack unifies the power of other track formats (e.g. GFF3, BED, WIG), and while optimised in size, adds more flexibility, customisation, and automation ("machine understandability").
Data format for a report of information derived from a biological pathway or network.
Biological pathway or network report format
Data format for annotation on a laboratory experiment.
Cytoband format for chromosome cytobands.
CellML, the format for mathematical models of biological and other networks.
Tabular Molecular Interaction format (MITAB), standardised by HUPO PSI MI.
Protein affinity format (PSI-PAR), standardised by HUPO PSI MI. It is compatible with PSI MI XML (MIF) and uses the same XML Schema.
mzML format for raw spectrometer output data, standardised by HUPO PSI MSS.
mzML is the successor and unifier of the mzData format developed by PSI and mzXML developed at the Seattle Proteome Center.
Format for mass pectra and derived data, include peptide sequences etc.
TraML (Transition Markup Language) is the format for mass spectrometry transitions, standardised by HUPO PSI MSS.
mzIdentML is the exchange format for peptides and proteins identified from mass spectra, standardised by HUPO PSI PI. It can be used for outputs of proteomics search engines.
mzQuantML is the format for quantitation values associated with peptides, proteins and small molecules from mass spectra, standardised by HUPO PSI PI. It can be used for outputs of quantitation software for proteomics.
GelML is the format for describing the process of gel electrophoresis, standardised by HUPO PSI PS.
spML is the format for describing proteomics sample processing, other than using gels, prior to mass spectrometric protein identification, standardised by HUPO PSI PS. It may also be applicable for metabolomics.
A human-readable encoding for the Web Ontology Language (OWL).
A syntax for writing OWL class expressions.
This format was influenced by the OWL Abstract Syntax and the DL style syntax.
A superset of the "Description-Logic Knowledge Representation System Specification from the KRSS Group of the ARPA Knowledge Sharing Effort".
The Terse RDF Triple Language (Turtle) is a human-friendly serialisation format for RDF (Resource Description Framework) graphs.
The SPARQL Query Language incorporates a very similar syntax.
A plain text serialisation format for RDF (Resource Description Framework) graphs, and a subset of the Turtle (Terse RDF Triple Language) format.
N-Triples should not be confused with Notation 3 which is a superset of Turtle.
A shorthand non-XML serialisation of Resource Description Framework model, designed with human-readability in mind.
Resource Description Framework (RDF) XML format.
RDF/XML is a serialisation syntax for OWL DL, but not for OWL Full.
The A2M format is used as the primary format for multiple alignments of protein or nucleic-acid sequences in the SAM suite of tools. It is a small modification of FASTA format for sequences and is compatible with most tools that read FASTA.
Standard flowgram format (SFF) is a binary file format used to encode results of pyrosequencing from the 454 Life Sciences platform for high-throughput sequencing.
The MAP file describes SNPs and is used by the Plink package.
The PED file describes individuals and genetic data and is used by the Plink package.
Data format for a metadata on an individual and their genetic data.
The PED/MAP file describes data used by the Plink package.
File format of a CT (Connectivity Table) file from the RNAstructure package.
Format for the Genetic Data Environment (GDE).
A multiple alignment in vertical format, as used in the AMPS (Alignment of Multiple Protein Sequences) pacakge.
HMMER profile HMM file for HMMER versions 2.x
HMMER profile HMM file for HMMER versions 3.x
XML format as produced by the NCBI Blast package
http://www.ebi.ac.uk/ena/software/cram-usage#format_specification http://samtools.github.io/hts-specs/CRAMv2.1.pdf
Reference-based compression of alignment format
JavaScript Object Notation format; a lightweight, text-based format to represent tree-structured data using key-value pairs.
Tabular data represented as tab-separated values in a text file.
Format of the cytoscape input file of gene expression ratios or values are specified over one or more experiments.
Bowtie format for indexed reference genome for "small" genomes.
RSF-format files contain one or more sequences that may or may not be related. In addition to the sequence data, each sequence can be annotated with descriptive sequence information (from the GCG manual).
Bioinformatics Sequence Markup Language format.
Bowtie format for indexed reference genome for "large" genomes.
Ensembl standard format for variation data.
Format of documents including word processor, spreadsheet and presentation.
Format used for images and image metadata.
Medical image format corresponding to the Digital Imaging and Communications in Medicine (DICOM) standard.
Medical image and metadata format of the Neuroimaging Informatics Technology Initiative.
Text-based tagged file format for medical images generated using the MetaImage software package.
Nearly Raw Rasta Data format designed to support scientific visualisation and image processing involving N-dimensional raster data.
File format used for scripts written in the R programming language for execution within the R software environment, typically for statistical computation and graphics.
File format used for scripts for the Statistical Package for the Social Sciences.
MHTML is not strictly an HTML format, it is encoded as an HTML email message (although with multipart/related instead of multipart/alternative). It, however, contains the main HTML block as its core, and thus it is for practical reasons incuded in EDAM as a specialisation of 'HTML'.
MIME HTML format for Web pages, which can include external resources, including images, Flash animations and so on.
Proprietary file format for (raw) BeadArray data used by genomewide profiling platforms from Illumina Inc. This format is output directly from the scanner and stores summary intensities for each probe-type on an array.
Joint Picture Group file format for lossy graphics file.
Sequence of segments with markers. Begins with byte of 0xFF and follows by marker type.
Reporter Code Count-A data file (.csv) output by the Nanostring nCounter Digital Analyzer, which contains gene sample information, probe information and probe counts.
ARFF (Attribute-Relation File Format) is an ASCII text file format that describes a list of instances sharing a set of attributes.
This file format is for machine learning.
AFG is a single text-based file assembly format that holds read and consensus information together
The bedGraph format allows display of continuous-valued data in track format. This display type is useful for probability scores and transcriptome data
Holds a tab-delimited chromosome /start /end / datavalue dataset.
Browser Extensible Data (BED) format of sequence annotation track that strictly does not contain non-standard fields beyond the first 3 columns.
Galaxy allows BED files to contain non-standard fields beyond the first 3 columns, some other implementations do not.
BED file format where each feature is described by chromosome, start, end, name, score, and strand.
Tab delimited data in strict BED format - no non-standard columns allowed; column count forced to 6
A BED file where each feature is described by all twelve columns.
Tab delimited data in strict BED format - no non-standard columns allowed; column count forced to 12
Tabular format of chromosome names and sizes used by Galaxy.
Custom Sequence annotation track format used by Galaxy.
Used for tracks/track views within galaxy.
Color space FASTA format sequence variant.
FASTA format extended for color space information.
HDF5 is a data model, library, and file format for storing and managing data, based on Hierarchical Data Format (HDF).
An HDF5 file appears to the user as a directed graph. The nodes of this graph are the higher-level HDF5 objects that are exposed by the HDF5 APIs: Groups, Datasets, Named datatypes. Currently supported by the Python MDTraj package.
HDF5 is the new version, according to the HDF group, a completely different technology (https://support.hdfgroup.org/products/hdf4/ compared to HDF.
The TIFF format is perhaps the most versatile and diverse bitmap format in existence. Its extensible nature and support for numerous data compression schemes allow developers to customize the TIFF format to fit any peculiar data storage needs.
Standard bitmap storage format in the Microsoft Windows environment.
Although it is based on Windows internal bitmap data structures, it is supported by many non-Windows and non-PC applications.
IM is a format used by LabEye and other applications based on the IFUNC image processing library.
IFUNC library reads and writes most uncompressed interchange versions of this format.
Photo CD format, which is the highest resolution format for images on a CD.
PCD was developed by Kodak. A PCD file contains five different resolution (ranging from low to high) of a slide or film negative. Due to it PCD is often used by many photographers and graphics professionals for high-end printed applications.
PCX is an image file format that uses a simple form of run-length encoding. It is lossless.
The PPM format is a lowest common denominator color image file format.
PSD (Photoshop Document) is a proprietary file that allows the user to work with the images' individual layers even after the file has been saved.
X BitMap is a plain text binary image format used by the X Window System used for storing cursor and icon bitmaps used in the X GUI.
The XBM format was replaced by XPM for X11 in 1989.
X PixMap (XPM) is an image file format used by the X Window System, it is intended primarily for creating icon pixmaps, and supports transparent pixels.
RGB file format is the native raster graphics file format for Silicon Graphics workstations.
The PBM format is a lowest common denominator monochrome file format. It serves as the common language of a large family of bitmap image conversion filters.
The PGM format is a lowest common denominator grayscale file format.
It is designed to be extremely easy to learn and write programs for.
PNG is a file format for image compression.
It iis expected to replace the Graphics Interchange Format (GIF).
Scalable Vector Graphics (SVG) is an XML-based vector image format for two-dimensional graphics with support for interactivity and animation.
The SVG specification is an open standard developed by the World Wide Web Consortium (W3C) since 1999.
Sun Raster is a raster graphics file format used on SunOS by Sun Microsystems
Textual report format for sequence quality for reports from sequencing machines.
FASTQ format subset for Phred sequencing quality score data only (no sequences).
Phred quality scores are defined as a property which is logarithmically related to the base-calling error probabilities.
FASTQ format subset for Phred sequencing quality score data only (no sequences) for Solexa/Illumina 1.0 format.
Solexa/Illumina 1.0 format can encode a Solexa/Illumina quality score from -5 to 62 using ASCII 59 to 126 (although in raw read data Solexa scores from -5 to 40 only are expected)
FASTQ format subset for Phred sequencing quality score data only (no sequences) from Illumina 1.5 and before Illumina 1.8.
Starting in Illumina 1.5 and before Illumina 1.8, the Phred scores 0 to 2 have a slightly different meaning. The values 0 and 1 are no longer used and the value 2, encoded by ASCII 66 "B", is used also at the end of reads as a Read Segment Quality Control Indicator.
FASTQ format subset for Phred sequencing quality score data only (no sequences) for SOLiD data.
For SOLiD data, the sequence is in color space, except the first position. The quality values are those of the Sanger format.
FASTQ format subset for Phred sequencing quality score data only (no sequences) from 454 sequencers.
Format that covers both the broad peak format and narrow peak format from ENCODE.
BAM files are compressed using a variant of GZIP (GNU ZIP), into a format called BGZF (Blocked GNU Zip Format).
TAB-delimited genome position file index format.
XML-based format used to store graph descriptions within Galaxy.
SIF (simple interaction file) Format - a network/pathway format used for instance in cytoscape.
MS Excel spreadsheet format consisting of a set of XML documents stored in a ZIP-compressed file.
Data format used by the SQLite database.
Data format used by the SQLite database conformant to the Gemini schema.
Duplicate of http://edamontology.org/format_3326
An index of a genome database, indexed for use by the snpeff tool.
Binary format used by MATLAB files to store workspace variables.
Network Common Data Form (NetCDF) library is supported by AMBER MD package from version 9.
Format used by netCDF software library for writing and reading chromatography-MS data files. Also used to store trajectory atom coordinates information, such as the ones obtained by Molecular Dynamics simulations.
Mascot Generic Format. Encodes multiple MS/MS spectra in a single file.
Files includes *m*/*z*, intensity pairs separated by headers; headers can contain a bit more information, including search engine instructions.
Spectral data format file where each spectrum is written to a separate file.
Each file contains one header line for the known or assumed charge and the mass of the precursor peptide ion, calculated from the measured *m*/*z* and the charge. This one line was then followed by all the *m*/*z*, intensity pairs that represent the spectrum.
Differ from .dta only in subtleties of the header line format and content and support the added feature of being able to.
Common file format for proteomics mass spectrometric data developed at the Seattle Proteome Center/Institute for Systems Biology.
Open data format for the storage, exchange, and processing of peptide sequence assignments of MS/MS scans, intended to provide a common data output format for many different MS/MS search engines and subsequent peptide-level analyses.
Graphical Pathway Markup Language (GPML) is an XML format used for exchanging biological pathways.
A list of k-mers and their occurences in a dataset. Can also be used as an implicit De Bruijn graph.
mzTab is a tab-delimited format for mass spectrometry-based proteomics and metabolomics results.
imzML metadata is a data format for mass spectrometry imaging metadata.
imzML data are recorded in 2 files: '.imzXML' is a metadata XML file based on mzML by HUPO-PSI, and '.ibd' is a binary file containing the mass spectra. This entry is for the metadata XML file
qcML is an XML format for quality-related data of mass spectrometry and other high-throughput measurements.
The focus of qcML is towards mass spectrometry based proteomics, but the format is suitable for metabolomics and sequencing as well.
PRIDE XML is an XML format for mass spectra, peptide and protein identifications, and metadata about a corresponding measurement, sample, experiment.
Simulation Experiment Description Markup Language (SED-ML) is an XML format for encoding simulation setups, according to the MIASE (Minimum Information About a Simulation Experiment) requirements.
Open Modeling EXchange format (OMEX) is a ZIPped format for encapsulating all information necessary for a modeling and simulation project in systems biology.
An OMEX file is a ZIP container that includes a manifest file, listing the content of the archive, an optional metadata file adding information about the archive and its content, and the files describing the model. OMEX is one of the standardised formats within COMBINE (Computational Modeling in Biology Network).
The Investigation / Study / Assay (ISA) tab-delimited (TAB) format incorporates metadata from experiments employing a combination of technologies.
ISA-TAB is based on MAGE-TAB. Other than tabular, the ISA model can also be represented in RDF, and in JSON (compliable with a set of defined JSON Schemata).
SBtab is a tabular format for biochemical network models.
Biological Connection Markup Language (BCML) is an XML format for biological pathways.
Biological Dynamics Markup Language (BDML) is an XML format for quantitative data describing biological dynamics.
Biological Expression Language (BEL) is a textual format for representing scientific findings in life sciences in a computable form.
SBGN-ML is an XML format for Systems Biology Graphical Notation (SBGN) diagrams of biological pathways or networks.
AGP is a tabular format for a sequence assembly (a contig, a scaffold/supercontig, or a chromosome).
SRA archive format (SRA) is the archive format used for input to the NCBI Sequence Read Archive.
VDB ('vertical database') is the native format used for export from the NCBI Sequence Read Archive.
Index file format used by the samtools package to index TAB-delimited genome position files.
A five-column, tab-delimited table of feature locations and qualifiers for importing annotation into an existing Sequin submission (an NCBI tool for submitting and updating GenBank entries).
Proprietary mass-spectrometry format of Thermo Scientific's ProteomeDiscoverer software.
This format corresponds to an SQLite database, and you can look into the files with e.g. SQLiteStudio3. There are also some readers (http://doi.org/10.1021/pr2005154) and converters (http://doi.org/10.1016/j.jprot.2015.06.015) for this format available, which re-engineered the database schema, but there is no official DB schema specification of Thermo Scientific for the format.
Exchange format of the Access to Biological Collections Data (ABCD) Schema; a standard for the access to and exchange of data about specimens and observations (primary biodiversity data).
Tab-delimited text files of GenePattern that contain a column for each sample, a row for each gene, and an expression value for each gene in each sample.
Mass spectrum file format from QSTAR and QTRAP instruments (ABI/Sciex).
Output format used by X! series search engines that is based on the XML language BIOML.
Proprietary file format for mass spectrometry data from Thermo Scientific.
Proprietary format for which documentation is not available.
"Raw" result file from Mascot database search.
Format of peak list files from Andromeda search engine (MaxQuant) that consist of arbitrarily many spectra.
Synthetic Biology Open Language (SBOL) is an XML format for the specification and exchange of biological design information in synthetic biology.
SBOL introduces a standardised format for the electronic exchange of information on the structural and functional aspects of biological designs.
PMML uses XML to represent mining models. The structure of the models is described by an XML Schema.
One or more mining models can be contained in a PMML document.
Image file format used by the Open Microscopy Environment (OME).
An OME-TIFF dataset consists of one or more files in standard TIFF or BigTIFF format, with the file extension .ome.tif or .ome.tiff, and an identical (or in the case of multiple files, nearly identical) string of OME-XML metadata embedded in the ImageDescription tag of each file's first IFD (Image File Directory). BigTIFF file extensions are also permitted, with the file extension .ome.tf2, .ome.tf8 or .ome.btf, but note these file extensions are an addition to the original specification, and software using an older version of the specification may not be able to handle these file extensions.
OME develops open-source software and data format standards for the storage and manipulation of biological microscopy data. It is a joint project between universities, research establishments, industry and the software development community.
The LocARNA PP format combines sequence or alignment information and (respectively, single or consensus) ensemble probabilities into an PP 2.0 record.
Format for multiple aligned or single sequences together with the probabilistic description of the (consensus) RNA secondary structure ensemble by probabilities of base pairs, base pair stackings, and base pairs and unpaired bases in the loop of base pairs.
Input format used by the Database of Genotypes and Phenotypes (dbGaP).
The Database of Genotypes and Phenotypes (dbGaP) is a National Institutes of Health (NIH) sponsored repository charged to archive, curate and distribute information produced by studies investigating the interaction of genotype and phenotype.
The BIological Observation Matrix (BIOM) is a format for representing biological sample by observation contingency tables in broad areas of comparative omics. The primary use of this format is to represent OTU tables and metagenome tables.
BIOM is a recognised standard for the Earth Microbiome Project, and is a project supported by Genomics Standards Consortium. Supported in QIIME, Mothur, MEGAN, etc.
A format for storage, exchange, and processing of protein identifications created from ms/ms-derived peptide sequence data.
No human-consumable information about this format is available (see http://tools.proteomecenter.org/wiki/index.php?title=Formats:protXML).
A linked data format enables publishing structured data as linked data (Linked Data), so that the data can be interlinked and become more useful through semantic queries.
JSON-LD, or JavaScript Object Notation for Linked Data, is a method of encoding Linked Data using JSON.
JavaScript Object Notation for Linked Data
YAML (YAML Ain't Markup Language) is a human-readable tree-structured data serialisation language.
Data in YAML format can be serialised into text, or binary format.
YAML version 1.2 is a superset of JSON; prior versions were "not strictly compatible".
Tabular data represented as values in a text file delimited by some character.
Tabular data represented as comma-separated values in a text file.
"Raw" result file from SEQUEST database search.
XML file format for files containing information about peptide identifications from mass spectrometry data analysis carried out with OpenMS.
Data table formatted such that it can be passed/streamed within the KNIME platform.
UniProtKB XML sequence features format is an XML format available for downloading UniProt entries.
UniProtKB RDF sequence features format is an RDF format available for downloading UniProt entries (in RDF/XML).
Work in progress. 'BioXSD' belongs to the 'BioXSD|GTrack' ecosystem of generic formats. 'BioJSON' is the JSON format based on the common, unified 'BioXSD data model', a.k.a. 'BioXSD|BioJSON|BioYAML'.
BioJSON is a BioXSD-schema-based JSON format of sequence-based data and some other common data - sequence records, alignments, feature records, references to resources, and more - optimised for integrative bioinformatics, web applications and APIs, and object-oriented programming.
Work in progress. 'BioXSD' belongs to the 'BioXSD|GTrack' ecosystem of generic formats. 'BioYAML' is the YAML format based on the common, unified 'BioXSD data model', a.k.a. 'BioXSD|BioJSON|BioYAML'.
BioYAML is a BioXSD-schema-based YAML format of sequence-based data and some other common data - sequence records, alignments, feature records, references to resources, and more - optimised for integrative bioinformatics, web APIs, human readability and editting, and object-oriented programming.
BioJSON is a JSON format of single multiple sequence alignments, with their annotations, features, and custom visualisation and application settings for the Jalview workbench.
'GSuite' belongs to the 'BioXSD|GTrack' ecosystem of generic formats, and particular to its subset, the 'GTrack ecosystem' (GTrack, GSuite, BTrack). 'GSuite' is the tabular format for an annotated collection of individual GTrack files.
GSuite is a tabular format for collections of genome or sequence feature tracks, suitable for integrative multi-track analysis. GSuite contains links to genome/sequence tracks, with additional metadata.
'BTrack' belongs to the 'BioXSD|GTrack' ecosystem of generic formats, and particular to its subset, the 'GTrack ecosystem' (GTrack, GSuite, BTrack). 'BTrack' is the binary, optionally compressed HDF5-based version of the GTrack and GSuite formats.
BTrack is an HDF5-based binary format for genome or sequence feature tracks and their collections, suitable for integrative multi-track analysis. BTrack is a binary, compressed alternative to the GTrack and GSuite formats.
Multi-Crop Passport Descriptors is a format available in 2 successive versions, V.1 (FAO/IPGRI 2001) and V.2 (FAO/Bioversity 2012).
The FAO/Bioversity/IPGRI Multi-Crop Passport Descriptors (MCPD) is an international standard format for exchange of germplasm information.
Data format of an annotated text, e.g. with recognised entities, concepts, and relations.
JSON format of annotated scientific text used by PubAnnotations and other tools.
BioC is a standardised XML format for sharing and integrating text data and annotations.
Native textual export format of annotated scientific text from PubTator.
A format of text annotation using the linked-data Open Annotation Data Model, serialised typically in RDF or JSON-LD.
A family of similar formats of text annotation, used by BRAT and other tools, known as BioNLP Shared Task format (BioNLP 2009 Shared Task on Event Extraction, BioNLP Shared Task 2011, BioNLP Shared Task 2013), BRAT format, BRAT standoff format, and similar.
A query language (format) for structured database queries.
SQL (Structured Query Language) is the de-facto standard query language (format of queries) for querying and manipulating data in relational databases.
XQuery (XML Query) is a query language (format of queries) for querying and manipulating structured and unstructured data, usually in the form of XML, text, and with vendor-specific extensions for other data formats (JSON, binary, etc.).
SPARQL (SPARQL Protocol and RDF Query Language) is a semantic query language for querying and manipulating data stored in Resource Description Framework (RDF) format.
The GEN file format contains genetic data and describes SNPs.
The SAMPLE file format contains information about each individual i.e. individual IDs, covariates, phenotypes and missing data proportions, from a GWAS study.
SDF is one of a family of chemical-data file formats developed by MDL Information Systems; it is intended especially for structural information.
An MDL Molfile is a file format for holding information about the atoms, bonds, connectivity and coordinates of a molecule.
Complete, portable representation of a SYBYL molecule. ASCII file which contains all the information needed to reconstruct a SYBYL molecule.
format for the LaTeX document preparation system
Tab-delimited text file format used by Eland - the read-mapping program distributed by Illumina with its sequencing analysis pipeline - which maps short Solexa sequence reads to the human reference genome.
Phylip multiple alignment sequence format, less stringent than PHYLIP format.
It differs from Phylip Format (format_1997) on length of the ID sequence. There no length restrictions on the ID, but whitespaces aren't allowed in the sequence ID/Name because one space separates the longest ID and the beginning of the sequence. Sequences IDs must be padded to the longest ID length.
Phylip multiple alignment sequence format, less stringent than PHYLIP sequential format (format_1998).
It differs from Phylip sequential format (format_1997) on length of the ID sequence. There no length restrictions on the ID, but whitespaces aren't allowed in the sequence ID/Name because one space separates the longest ID and the beginning of the sequence. Sequences IDs must be padded to the longest ID length.
Default XML format of VisANT, containing all the network information.
GML (Graph Modeling Language) is a text file format supporting network data with a very easy syntax. It is used by Graphlet, Pajek, yEd, LEDA and NetworkX.
FASTG is a format for faithfully representing genome assemblies in the face of allelic polymorphism and assembly uncertainty.
It is called FASTG, like FASTA, but the G stands for "graph".
Data format for raw data from a nuclear magnetic resonance (NMR) spectroscopy experiment.
Nuclear magnetic resonance spectroscopy data format
nmrML is an MSI supported XML-based open access format for metabolomics NMR raw and processed spectral data. It is accompanies by an nmrCV (controlled vocabulary) to allow ontology-based annotations.
. proBAM is an adaptation of BAM (format_2572), which was extended to meet specific requirements entailed by proteomics data.
. proBED is an adaptation of BED (format_3003), which was extended to meet specific requirements entailed by proteomics data.
GenePix Results (GPR) text file format developed by Axon Instruments that is used to save GenePix Results data.
Binary format used by the ARB software suite
OpenMS format for grouping features in one map or across several maps.
OpenMS format for quantitation results (LC/MS features).
Now deprecated data format of the HUPO Proteomics Standards Initiative. Replaced by mzML (format_3244).
Format supported by the Tide tool for identifying peptides from tandem mass spectra.
XML format as produced by the NCBI Blast package v2.
ibd is a data format for mass spectrometry imaging data.
imzML data is recorded in 2 files: '.imzXML' is a metadata XML file based on mzML by HUPO-PSI, and '.ibd' is a binary file containing the mass spectra.
Data format used in Natural Language Processing.
XML input file format for BEAST Software (Bayesian Evolutionary Analysis Sampling Trees).
Chado-XML format is a direct mapping of the Chado relational schema into XML.
An alignment format generated by PRANK/PRANKSTER consisting of four elements: newick, nodes, selection and model.
Output xml file from the InterProScan sequence analysis application.
The KEGG Markup Language (KGML) is an exchange format of the KEGG pathway maps, which is converted from internally used KGML+ (KGML+SVG) format.
XML format for collected entries from biobliographic databases MEDLINE and PubMed.
A set of XML compliant markup components for describing multiple sequence alignments.
OrthoXML is designed broadly to allow the storage and comparison of orthology data from any ortholog database. It establishes a structure for describing orthology relationships while still allowing flexibility for database-specific information to be encapsulated in the same format.
Tree structure of Protein Sequence Database Markup Language generated using Matra software.
SeqXML is an XML Schema to describe biological sequences, developed by the Stockholm Bioinformatics Centre.
XML format for the UniRef reference clusters.
Common Workflow Language (CWL) format for description of command-line tools and workflows.
Proprietary file format for mass spectrometry data from Waters.
Proprietary format for which documentation is not available, but used by multiple tools.
A standardized file format for data exchange in mass spectrometry, initially developed for infrared spectrometry.
JCAMP-DX is an ASCII based format and therefore not very compact even though it includes standards for file compression.
An NLP format used for annotated textual documents.
NLP format used by a specific type of corpus (collection of texts).
mirGFF3 is a common format for microRNA data resulting from small-RNA RNA-Seq workflows.
mirGFF3 is a specialisation of GFF3; produced by small-RNA-Seq analysis workflows, usable and convertible with the miRTop API (https://mirtop.readthedocs.io/en/latest/), and consumable by tools for downstream analysis.
A "placeholder" concept for formats of annotated RNA data, including e.g. microRNA and RNA-Seq data.
File format to store trajectory information for a 3D structure .
Formats differ on what they are able to store (coordinates, velocities, topologies) and how they are storing it (raw, compressed, textual, binary).
Binary file format to store trajectory information for a 3D structure .
Textual file format to store trajectory information for a 3D structure .
HDF is the name of a set of file formats and libraries designed to store and organize large amounts of numerical data, originally developed at the National Center for Supercomputing Applications at the University of Illinois.
HDF is currently supported by many commercial and non-commercial software platforms such as Java, MATLAB/Scilab, Octave, Python and R.
PCAZip format is a binary compressed file to store atom coordinates based on Essential Dynamics (ED) and Principal Component Analysis (PCA).
The compression is made projecting the Cartesian snapshots collected along the trajectory into an orthogonal space defined by the most relevant eigenvectors obtained by diagonalization of the covariance matrix (PCA). In the compression/decompression process, part of the original information is lost, depending on the final number of eigenvectors chosen. However, with a reasonable choice of the set of eigenvectors the compression typically reduces the trajectory file to less than one tenth of their original size with very acceptable loss of information. Compression with PCAZip can only be applied to unsolvated structures.
Portable binary format for trajectories produced by GROMACS package.
XTC uses the External Data Representation (xdr) routines for writing and reading data which were created for the Unix Network File System (NFS). XTC files use a reduced precision (lossy) algorithm which works multiplying the coordinates by a scaling factor (typically 1000), so converting them to pm (GROMACS standard distance unit is nm). This allows an integer rounding of the values. Several other tricks are performed, such as making use of atom proximity information: atoms close in sequence are usually close in space (e.g. water molecules). That makes XTC format the most efficient in terms of disk usage, in most cases reducing by a factor of 2 the size of any other binary trajectory format.
Trajectory Next Generation (TNG) is a format for storage of molecular simulation data. It is designed and implemented by the GROMACS development group, and it is called to be the substitute of the XTC format.
Fully architecture-independent format, regarding both endianness and the ability to mix single/double precision trajectories and I/O libraries. Self-sufficient, it should not require any other files for reading, and all the data should be contained in a single file for easy transport. Temporal compression of data, improving the compression rate of the previous XTC format. Possibility to store meta-data with information about the simulation. Direct access to a particular frame. Efficient parallel I/O.
The XYZ chemical file format is widely supported by many programs, although many slightly different XYZ file formats coexist (Tinker XYZ, UniChem XYZ, etc.). Basic information stored for each atom in the system are x, y and z coordinates and atom element/atomic number.
XYZ files are structured in this way: First line contains the number of atoms in the file. Second line contains a title, comment, or filename. Remaining lines contain atom information. Each line starts with the element symbol, followed by x, y and z coordinates in angstroms separated by whitespace. Multiple molecules or frames can be contained within one file, so it supports trajectory storage. XYZ files can be directly represented by a molecular viewer, as they contain all the basic information needed to build the 3D model.
AMBER trajectory (also called mdcrd), with 10 coordinates per line and format F8.3 (fixed point notation with field width 8 and 3 decimal places).
Format of topology files; containing the static information of a structure molecular system that is needed for a molecular simulation.
Many different file formats exist describing structural molecular topology. Tipically, each MD package or simulation software works with their own implementation (e.g. GROMACS top, CHARMM psf, AMBER prmtop).
GROMACS MD package top textual files define an entire structure system topology, either directly, or by including itp files.
There is currently no tool available for conversion between GROMACS topology format and other formats, due to the internal differences in both approaches. There is, however, a method to convert small molecules parameterized with AMBER force-field into GROMACS format, allowing simulations of these systems with GROMACS MD package.
AMBER Prmtop file (version 7) is a structure topology text file divided in several sections designed to be parsed easily using simple Fortran code. Each section contains particular topology information, such as atom name, charge, mass, angles, dihedrals, etc.
It can be modified manually, but as the size of the system increases, the hand-editing becomes increasingly complex. AMBER Parameter-Topology file format is used extensively by the AMBER software suite and is referred to as the Prmtop file for short.
version 7 is written to distinguish it from old versions of AMBER Prmtop. Similarly to HDF5, it is a completely different format, according to AMBER group: a drastic change to the file format occurred with the 2004 release of Amber 7 (http://ambermd.org/prmtop.pdf)
X-Plor Protein Structure Files (PSF) are structure topology files used by NAMD and CHARMM molecular simulations programs. PSF files contain six main sections of interest: atoms, bonds, angles, dihedrals, improper dihedrals (force terms used to maintain planarity) and cross-terms.
The high similarity in the functional form of the two potential energy functions used by AMBER and CHARMM force-fields gives rise to the possible use of one force-field within the other MD engine. Therefore, the conversion of PSF files to AMBER Prmtop format is possible with the use of AMBER chamber (CHARMM - AMBER) program.
GROMACS itp files (include topology) contain structure topology information, and are tipically included in GROMACS topology files (GROMACS top). Itp files are used to define individual (or multiple) components of a topology as a separate file. This is particularly useful if there is a molecule that is used frequently, and also reduces the size of the system topology file, splitting it in different parts.
GROMACS itp files are used also to define position restrictions on the molecule, or to define the force field parameters for a particular ligand.
Format of force field parameter files, which store the set of parameters (charges, masses, radii, bond lengths, bond dihedrals, etc.) that are essential for the proper description and simulation of a molecular system.
Many different file formats exist describing force field parameters. Tipically, each MD package or simulation software works with their own implementation (e.g. GROMACS itp, CHARMM rtf, AMBER off / frcmod).
Scripps Research Institute BinPos format is a binary formatted file to store atom coordinates.
It is basically a translation of the ASCII atom coordinate format to binary code. The only additional information stored is a magic number that identifies the BinPos format and the number of atoms per snapshot. The remainder is the chain of coordinates binary encoded. A drawback of this format is its architecture dependency. Integers and floats codification depends on the architecture, thus it needs to be converted if working in different platforms (little endian, big endian).
AMBER coordinate/restart file with 6 coordinates per line and decimal format F12.7 (fixed point notation with field width 12 and 7 decimal places)
Format of CHARMM Residue Topology Files (RTF), which define groups by including the atoms, the properties of the group, and bond and charge information.
AMBER frcmod (Force field Modification) is a file format to store any modification to the standard force field needed for a particular molecule to be properly represented in the simulation.
AMBER Object File Format library files (OFF library files) store residue libraries (forcefield residue parameters).
MReData is a text based data standard for processed NMR data. It is relying on SDF molecule data and allows to store assignments of NMR peaks to molecule features. The NMR-extracted data (or "NMReDATA") includes: Chemical shift,scalar coupling, 2D correlation, assignment, etc.
NMReData is a text based data standard for processed NMR data. It is relying on SDF molecule data and allows to store assignments of NMR peaks to molecule features. The NMR-extracted data (or "NMReDATA") includes: Chemical shift,scalar coupling, 2D correlation, assignment, etc. Find more in the paper at D. Jeannerat, Magn. Reson. in Chem., 2017, 55, 7-14.
BpForms is a string format for concretely representing the primary structures of biopolymers, including DNA, RNA, and proteins that include non-canonical nucleic and amino acids. See https://www.bpforms.org for more information.
The first 4 bytes of any trr file containing 1993. See https://github.com/galaxyproject/galaxy/pull/6597/files#diff-409951594551183dbf886e24de6cb129R760
Format of trr files that contain the trajectory of a simulation experiment used by GROMACS.
Mash sketch is a format for sequence / sequence checksum information. To make a sketch, each k-mer in a sequence is hashed, which creates a pseudo-random identifier. By sorting these hashes, a small subset from the top of the sorted list can represent the entire sequence.
The Loom file format is based on HDF5, a standard for storing large numerical datasets. The Loom format is designed to efficiently hold large omics datasets. Typically, such data takes the form of a large matrix of numbers, along with metadata for the rows and columns.
The Zarr format is an implementation of chunked, compressed, N-dimensional arrays for storing data.
The Matrix Market matrix (MTX) format stores numerical or pattern matrices in a dense (array format) or sparse (coordinate format) representation.
BcForms is a format for abstractly describing the molecular structure (atoms and bonds) of macromolecular complexes as a collection of subunits and crosslinks. Each subunit can be described with BpForms (http://edamontology.org/format_3909) or SMILES (http://edamontology.org/data_2301). BcForms uses an ontology of crosslinks to abstract the chemical details of crosslinks from the descriptions of complexes (see https://bpforms.org/crosslink.html).
BcForms is related to http://edamontology.org/format_3909. (BcForms uses BpForms to describe subunits which are DNA, RNA, or protein polymers.) However, that format isn't the parent of BcForms. BcForms is similarly related to SMILES (http://edamontology.org/data_2301).
N-Quads is a line-based, plain text format for encoding an RDF dataset. It includes information about the graph each triple belongs to.
N-Quads should not be confused with N-Triples which does not contain graph information.
Vega is a visualization grammar, a declarative language for creating, saving, and sharing interactive visualization designs. With Vega, you can describe the visual appearance and interactive behavior of a visualization in a JSON format, and generate web-based views using Canvas or SVG.
Vega-Lite is a high-level grammar of interactive graphics. It provides a concise JSON syntax for rapidly generating visualizations to support analysis. Vega-Lite specifications can be compiled to Vega specifications.
A model description language for computational neuroscience.
BioNetGen is a format for the specification and simulation of rule-based models of biochemical systems, including signal transduction, metabolic, and genetic regulatory networks.
A Docker image is a file, comprised of multiple layers, that is used to execute code in a Docker container. An image is essentially built from the instructions for a complete and executable version of an application, which relies on the host OS kernel.
Graphical Fragment Assembly captures sequence graphs as the product of an assembly, a representation of variation in genomes, splice graphs in genes, or even overlap between reads from long-read sequencing technology.
ObjTables is a toolkit for creating re-usable datasets that are both human and machine-readable, combining the ease of spreadsheets (e.g., Excel workbooks) with the rigor of schemas (classes, their attributes, the type of each attribute, and the possible relationships between instances of classes). ObjTables consists of a format for describing schemas for spreadsheets, numerous data types for science, a syntax for indicating the class and attribute represented by each table and column in a workbook, and software for using schemas to rigorously validate, merge, split, compare, and revision datasets.
The CONTIG format used for output of the SOAPdenovo alignment program. It contains contig sequences generated without using mate pair information.
WEGO native format used by the Web Gene Ontology Annotation Plot application. Tab-delimited format with gene names and others GO IDs (columns) with one annotation record per line.
Tab-delimited format for gene expression levels table, calculated as Reads Per Kilobase per Million (RPKM) mapped reads.
For example a 1kb transcript with 1000 alignments in a sample of 10 million reads (out of which 8 million reads can be mapped) will have RPKM = 1000/(1 * 8) = 125
TAR archive file format generated by the Unix-based utility tar.
The CHAIN format describes a pairwise alignment that allow gaps in both sequences simultaneously and is used by the UCSC Genome Browser.
The NET file format is used to describe the data that underlie the net alignment annotations in the UCSC Genome Browser.
Format of QMAP files generated for methylation data from an internal BGI pipeline.
An emerging format for high-level Galaxy workflow description.
The proprietary native video format of various Microsoft programs such as Windows Media Player.
ZIP is an archive file format that supports lossless data compression.
A ZIP file may contain one or more files or directories that may have been compressed.
Zeiss' proprietary image format based on TIFF.
LSM files are the default data export for the Zeiss LSM series confocal microscopes (e.g. LSM 510, LSM 710). In addition to the image data, LSM files contain most imaging settings.
GNU zip compressed file format common to Unix-based operating systems.
Audio Video Interleaved (AVI) format is a multimedia container format for AVI files, that allows synchronous audio-with-video playback.
A declaration file format for UCSC browsers track dataset display charateristics.
Compact Idiosyncratic Gapped Alignment Report format is a compressed (run-length encoded) pairwise alignment format. It is useful for representing long (e.g. genomic) pairwise alignments.
STL is a file format native to the stereolithography CAD software created by 3D Systems. The format is used to save and share surface-rendered 3D images and also for 3D printing.
U3D (Universal 3D) is a compressed file format and data structure for 3D computer graphics. It contains 3D model information such as triangle meshes, lighting, shading, motion data, lines and points with color and structure.
Bitmap image format used for storing textures.
Texture files can create the appearance of different surfaces and can be applied to both 2D and 3D objects. Note the file extension .tex is also used for LaTex documents which are a completely different format and they are NOT interchangable.
Format for scripts writtenin Python - a widely used high-level programming language for general-purpose programming.
A digital multimedia container format most commonly used to store video and audio.
Format for scripts written in Perl - a family of high-level, general-purpose, interpreted, dynamic programming languages.
Format for scripts written in the R language - an open source programming language and software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing.
A file format for making dynamic documents (R Markdown scripts) with the R language.
An open file format from the Neuroimaging Informatics Technology Initiative (NIfTI) commonly used to store brain imaging data obtained using Magnetic Resonance Imaging (MRI) methods.
Format used by Python pickle module for serializing and de-serializing a Python object structure.
The standard binary file format used by NumPy - a fundamental package for scientific computing with Python - for persisting a single arbitrary NumPy array on disk. The format stores all of the shape and dtype information necessary to reconstruct the array correctly.
Format of repertoire (archive) files that can be read by SimToolbox (a MATLAB toolbox for structured illumination fluorescence microscopy) or alternatively extracted with zip file archiver software.
A configuration file used by various programs to store settings that are specific to their respective software.
Format used by the Zstandard real-time compression algorith.
The file format for MATLAB scripts or functions.
A function that processes a set of inputs and results in a set of outputs, or associates arguments (inputs) with values (outputs).
Special cases are: a) An operation that consumes no input (has no input arguments). Such operation is either a constant function, or an operation depending only on the underlying state. b) An operation that may modify the underlying state but has no output. c) The singular-case operation with no input or output, that still may modify the underlying state.
Operation is a function that is computational. It typically has input(s) and output(s), which are always data.
Computational tool provides one or more operations.
Process can have a function (as its quality/attribute), and can also perform an operation with inputs and outputs.
Search or query a data resource and retrieve entries and / or annotation.
Search database to retrieve all relevant references to a particular entity or entry.
Data retrieval (database cross-reference)
Annotate an entity (typically a biological or biomedical database entity) with terms from a controlled vocabulary.
This is a broad concept and is used a placeholder for other, more specific concepts.
Generate an index of (typically a file of) biological data.
Retrieve basic information about a molecular sequence.
Generate a molecular sequence by some means.
Edit or change a molecular sequence, either randomly or specifically.
Merge two or more (typically overlapping) molecular sequences.
Convert a molecular sequence from one type to another.
Calculate sequence complexity, for example to find low-complexity regions in sequences.
Calculate sequence ambiguity, for example identity regions in protein or nucleotide sequences with many ambiguity codes.
Calculate character or word composition or frequency of a molecular sequence.
Find and/or analyse repeat sequences in (typically nucleotide) sequences.
Repeat sequences include tandem repeats, inverted or palindromic repeats, DNA microsatellites (Simple Sequence Repeats or SSRs), interspersed repeats, maximal duplications and reverse, complemented and reverse complemented repeats etc. Repeat units can be exact or imperfect, in tandem or dispersed, of specified or unspecified length.
Discover new motifs or conserved patterns in sequences or sequence alignments (de-novo discovery).
Motifs and patterns might be conserved or over-represented (occur with improbable frequency).
Find (scan for) known motifs, patterns and regular expressions in molecular sequence(s).
Find motifs shared by molecular sequences.
Analyse the sequence, conformational or physicochemical properties of transcription regulatory elements in DNA sequences.
For example transcription factor binding sites (TFBS) analysis to predict accessibility of DNA to binding factors.
Transcription regulatory sequence analysis
Identify common, conserved (homologous) or synonymous transcriptional regulatory motifs (transcription factor binding sites).
Conserved transcription regulatory sequence identification
Extract, calculate or predict non-positional (physical or chemical) properties of a protein from processing a protein (3D) structure.
Protein property calculation (from structure)
Analyse flexibility and motion in protein structure.
Use this concept for analysis of flexible and rigid residues, local chain deformability, regions undergoing conformational change, molecular vibrations or fluctuational dynamics, domain motions or other large-scale structural transitions in a protein structure.
Identify or screen for 3D structural motifs in protein structure(s).
Protein structural feature identification
This includes conserved substructures and conserved geometry, such as spatial arrangement of secondary structure or protein backbone. Methods might use structure alignment, structural templates, searches for similar electrostatic potential and molecular surface shape, surface-mapping of phylogenetic information etc.
Identify structural domains in a protein structure from first principles (for example calculations on structural compactness).
Analyse the architecture (spatial arrangement of secondary structure) of protein structure(s).
Calculate or extract inter-atomic, inter-residue or residue-atom contacts, distances and interactions in protein structure(s).
Calculate, visualise or analyse phi/psi angles of a protein structure.
Extract, calculate or predict non-positional (physical or chemical) properties of a protein, including any non-positional properties of the molecular sequence, from processing a protein sequence or 3D structure.
Protein property calculation (from sequence)
This includes methods to render and visualise the properties of a protein sequence, and a residue-level search for properties such as solvent accessibility, hydropathy, secondary structure, ligand-binding etc.
Predict antigenicity, allergenicity / immunogenicity, allergic cross-reactivity etc of peptides and proteins.
B cell peptide immunogenicity prediction
Immunological system are cellular or humoral. In vaccine design to induces a cellular immune response, methods must search for antigens that can be recognized by the major histocompatibility complex (MHC) molecules present in T lymphocytes. If a humoral response is required, antigens for B cells must be identified.
This includes methods that generate a graphical rendering of antigenicity of a protein, such as a Hopp and Woods plot.
This is usually done in the development of peptide-specific antibodies or multi-epitope vaccines. Methods might use sequence data (for example motifs) and / or structural data.
Predict, recognise and identify positional features in molecular sequences such as key functional sites or regions.
Look at "Protein feature detection" (http://edamontology.org/operation_3092) and "Nucleic acid feature detection" (http://edamontology.org/operation_0415) in case more specific terms are needed.
Extract a sequence feature table from a sequence database entry.
Query the features (in a feature table) of molecular sequence(s).
Compare the feature tables of two or more molecular sequences.
Display basic information about a sequence alignment.
Compare (typically by aligning) two molecular sequence alignments.
Convert a molecular sequence alignment from one type to another (for example amino acid to coding nucleotide sequence).
Process (read and / or write) physicochemical property data of nucleic acids.
Calculate or predict physical or chemical properties of nucleic acid molecules, including any non-positional properties of the molecular sequence.
Predict splicing alternatives or transcript isoforms from analysis of sequence data.
Detect frameshifts in DNA sequences, including frameshift sites and signals, and frameshift errors from sequencing projects.
Methods include sequence alignment (if related sequences are available) and word-based sequence comparison.
Detect vector sequences in nucleotide sequence, typically by comparison to a set of known vector sequences.
Predict secondary structure of protein sequences.
Secondary structure prediction (protein)
Methods might use amino acid composition, local sequence information, multiple sequence alignments, physicochemical features, estimated energy content, statistical algorithms, hidden Markov models, support vector machines, kernel machines, neural networks etc.
Predict super-secondary structure of protein sequence(s).
Protein super-secondary structure prediction
Predict and/or classify transmembrane proteins or transmembrane (helical) domains or regions in protein sequences.
Analyse transmembrane protein(s), typically by processing sequence and / or structural data, and write an informative report for example about the protein and its transmembrane domains / regions.
Use this (or child) concept for analysis of transmembrane domains (buried and exposed faces), transmembrane helices, helix topology, orientation, inter-helical contacts, membrane dipping (re-entrant) loops and other secondary structure etc. Methods might use pattern discovery, hidden Markov models, sequence alignment, structural profiles, amino acid property analysis, comparison to known domains or some combination (hybrid methods).
This is a "organisational class" not very useful for annotation per se.
Predict tertiary structure of a molecular (biopolymer) sequence.
Predict contacts, non-covalent interactions and distance (constraints) between amino acids in protein sequences.
Methods usually involve multiple sequence alignment analysis.
Analyse experimental protein-protein interaction data from for example yeast two-hybrid analysis, protein microarrays, immunoaffinity chromatography followed by mass spectrometry, phage display etc.
Identify or predict protein-protein interactions, interfaces, binding sites etc in protein sequences.
Protein-protein interaction prediction (from protein sequence)
Identify or predict protein-protein interactions, interfaces, binding sites etc in protein structures.
Protein-protein interaction prediction (from protein structure)
Analyse a network of protein interactions.
Notions of pathway and network were mixed up, EDAM 1.24 disentangles them.
Compare two or more biological pathways or networks.
Predict RNA secondary structure (for example knots, pseudoknots, alternative structures etc).
Methods might use RNA motifs, predicted intermolecular contacts, or RNA sequence-structure compatibility (inverse RNA folding).
Analyse some aspect of RNA/DNA folding, typically by processing sequence and/or structural data. For example, compute folding energies such as minimum folding energies for DNA or RNA sequences or energy landscape of RNA mutants.
Retrieve information on restriction enzymes or restriction enzyme sites.
Data retrieval (restriction enzyme annotation)
Identify genetic markers in DNA sequences.
A genetic marker is any DNA sequence of known chromosomal location that is associated with and specific to a particular gene or trait. This includes short sequences surrounding a SNP, Sequence-Tagged Sites (STS) which are well suited for PCR amplification, a longer minisatellites sequence etc.
Generate a genetic (linkage) map of a DNA sequence (typically a chromosome) showing the relative positions of genetic markers based on estimation of non-physical distances.
Mapping involves ordering genetic loci along a chromosome and estimating the physical distance between loci. A genetic map shows the relative (not physical) position of known genes and genetic markers.
This includes mapping of the genetic architecture of dynamic complex traits (functional mapping), e.g. by characterisation of the underlying quantitative trait loci (QTLs) or nucleotides (QTNs).
For example, estimate how close two genes are on a chromosome by calculating how often they are transmitted together to an offspring, ascertain whether two genes are linked and parental linkage, calculate linkage map distance etc.
Calculate codon usage statistics and create a codon usage table.
Analyse codon usage in molecular sequences or process codon usage data (e.g. a codon usage table).
Identify and plot third base position variability in a nucleotide sequence.
Find exact character or word matches between molecular sequences without full sequence alignment.
Calculate a sequence distance matrix or otherwise estimate genetic distances between molecular sequences.
Compare two or more molecular sequences, identify and remove redundant sequences based on some criteria.
Build clusters of similar sequences, typically using scores from pair-wise alignment or other comparison of the sequences.
The clusters may be output or used internally for some other purpose.
Includes methods that align sequence profiles (representing sequence alignments): ethods might perform one-to-one, one-to-many or many-to-many comparisons. See also 'Sequence alignment comparison'.
Align (identify equivalent sites within) molecular sequences.
Multiple sequence alignment (constrained)
Align two or more molecular sequences of different types (for example genomic DNA to EST, cDNA or mRNA).
Align molecular sequences using sequence and structural information.
Includes methods that align structural (3D) profiles or templates (representing structures or structure alignments) - including methods that perform one-to-one, one-to-many or many-to-many comparisons.
Align (superimpose) molecular tertiary structures.
Generate some type of sequence profile (for example a hidden Markov model) from a sequence alignment.
Generate some type of structural (3D) profile or template from a structure or structure alignment.
Align sequence profiles (representing sequence alignments).
Align structural (3D) profiles or templates (representing structures or structure alignments).
Align molecular sequence(s) to sequence profile(s), or profiles to other profiles. A profile typically represents a sequence alignment.
A sequence profile typically represents a sequence alignment. Methods might perform one-to-one, one-to-many or many-to-many comparisons.
Align molecular sequence(s) to structural (3D) profile(s) or template(s) (representing a structure or structure alignment).
This includes sequence-to-3D-profile alignment methods, which align molecular sequence(s) to structural (3D) profile(s) or template(s) (representing a structure or structure alignment) - methods might perform one-to-one, one-to-many or many-to-many comparisons.
Align molecular sequence to structure in 3D space (threading).
Use this concept for methods that evaluate sequence-structure compatibility by assessing residue interactions in 3D. Methods might perform one-to-one, one-to-many or many-to-many comparisons.
Recognize (predict and identify) known protein structural domains or folds in protein sequence(s) which (typically) are not accompanied by any significant sequence similarity to know structures.
(jison)Too fine-grained, the operation (Data retrieval) hasn't changed, just what is retrieved.
Search for and retrieve data concerning or describing some core data, as distinct from the primary data that is being described.
This includes documentation, general information and other metadata on entities such as databases, database entries and tools.
Query scientific literature, in search for articles, article data, concepts, named entities, or for statistics.
Process and analyse text (typically scientific literature) to extract information from it.
Design or predict oligonucleotide primers for PCR and DNA amplification etc.
PCR primer design (based on gene structure)
PCR primer design (for conserved primers)
PCR primer design (for gene transcription profiling)
PCR primer design (for genotyping polymorphisms)
PCR primer design (for large scale sequencing)
PCR primer design (for methylation PCRs)
Primer design involves predicting or selecting primers that are specific to a provided PCR template. Primers can be designed with certain properties such as size of product desired, primer size etc. The output might be a minimal or overlapping primer set.
This includes predicting primers based on gene structure, promoters, exon-exon junctions, predicting primers that are conserved across multiple genomes or species, primers for for gene transcription profiling, for genotyping polymorphisms, for example single nucleotide polymorphisms (SNPs), for large scale sequencing, or for methylation PCRs.
Predict and/or optimize oligonucleotide probes for DNA microarrays, for example for transcription profiling of genes, or for genomes and gene families.
Combine (align and merge) overlapping fragments of a DNA sequence to reconstruct the original sequence.
For example, assemble overlapping reads from paired-end sequencers into contigs (a contiguous sequence corresponding to read overlaps). Or assemble contigs, for example ESTs and genomic DNA fragments, depending on the detected fragment overlaps.
Standardize or normalize microarray data.
Microarray data standardisation and normalisation
Process (read and / or write) SAGE, MPSS or SBS experimental data.
Sequencing-based expression profile data processing
Perform cluster analysis of expression data to identify groups with similar expression profiles, for example by clustering.
The measurement of the activity (expression) of multiple genes in a cell, tissue, sample etc., in order to get an impression of biological function.
Gene expression profiling generates some sort of gene expression profile, for example from microarray data.
Interpret (in functional terms) and annotate gene expression data.
For example, identify full-length cDNAs from EST sequences or detect potential EST antisense transcripts.
Identify and select targets for protein structural determination.
Methods will typically navigate a graph of protein families of known structure.
Includes secondary structure assignment from circular dichroism (CD) spectroscopic data, and from protein coordinate data.
Assign secondary structure from protein coordinate or experimental data.
Assign a protein tertiary structure (3D coordinates), or other aspects of protein structure, from raw experimental data.
Evaluate the quality or correctness a protein three-dimensional model.
Model validation might involve checks for atomic packing, steric clashes (bumps), volume irregularities, agreement with electron density maps, number of amino acid residues, percentage of residues with missing or bad atoms, irregular Ramachandran Z-scores, irregular Chi-1 / Chi-2 normality scores, RMS-Z score on bonds and angles etc.
The PDB file format has had difficulties, inconsistencies and errors. Corrections can include identifying a meaningful sequence, removal of alternate atoms, correction of nomenclature problems, removal of incomplete residues and spurious waters, addition or removal of water, modelling of missing side chains, optimisation of cysteine bonds, regularisation of bond lengths, bond angles and planarities etc.
This includes methods that calculate poor quality residues. The scoring function to identify poor quality residues may consider residues with bad atoms or atoms with high B-factor, residues in the N- or C-terminal position, adjacent to an unstructured residue, non-canonical residues, glycine and proline (or adjacent to these such residues).
Refine (after evaluation) a model of a molecular structure (typically a protein structure) to reduce steric clashes, volume irregularities etc.
Phylogenetic trees are usually constructed from a set of sequences from which an alignment (or data matrix) is calculated.
Analyse an existing phylogenetic tree or trees, typically to detect features or make predictions.
Phylgenetic modelling is the modelling of trait evolution and prediction of trait values using phylogeny as a basis.
For example, to produce a consensus tree, subtrees, supertrees, calculate distances between trees or test topological similarity between trees (e.g. a congruence index) etc.
Comparison of a DNA sequence to orthologous sequences in different species and inference of a phylogenetic tree, in order to identify regulatory elements such as transcription factor binding sites (TFBS).
Phylogenetic shadowing is a type of footprinting where many closely related species are used. A phylogenetic 'shadow' represents the additive differences between individual sequences. By masking or 'shadowing' variable positions a conserved sequence is produced with few or none of the variations, which is then compared to the sequences of interest to identify significant regions of conservation.
Predict the folding pathway(s) or non-native structural intermediates of a protein.
Map and model the effects of single nucleotide polymorphisms (SNPs) on protein structure(s).
Predict the effect of point mutation on a protein structure, in terms of strucural effects and protein folding, stability and function.
Protein SNP mapping maps and modesl the effects of single nucleotide polymorphisms (SNPs) on protein structure(s). Methods might predict silent or pathological mutations.
Design molecules that elicit an immune response (immunogens).
Predict and optimise zinc finger protein domains for DNA/RNA binding (for example for transcription factors and nucleases).
Calculate Km, Vmax and derived data for an enzyme reaction.
Reformat a file of data (or equivalent entity in memory).
Test and validate the format and content of a data file.
Visualise, plot or render (graphically) biomolecular data such as molecular sequences or structures.
This includes methods to render and visualise molecules.
Search a sequence database by sequence comparison and retrieve similar sequences. sequences matching a given sequence motif or pattern, such as a Prosite pattern or regular expression.
This excludes direct retrieval methods (e.g. the dbfetch program).
Search a tertiary structure database, typically by sequence and/or structure comparison, or some other means, and retrieve structures and associated data.
Search a secondary protein database (of classification information) to assign a protein sequence(s) to a known protein family or group.
Screen a sequence against a motif or pattern database.
Search a database of sequence profiles with a query sequence.
Search a database of transmembrane proteins, for example for sequence or structural similarities.
Query a database and retrieve sequences with a given entry code or accession number.
Query a database and retrieve sequences containing a given keyword.
Search a sequence database and retrieve sequences that are similar to a query sequence.
Search a sequence database and retrieve sequences matching a given sequence motif or pattern, such as a Prosite pattern or regular expression.
Sequence database search (by motif or pattern)
Search a sequence database and retrieve sequences of a given amino acid composition.
Sequence database search (by amino acid composition)
Search a sequence database and retrieve sequences with a specified property, typically a physicochemical or compositional property.
Search a sequence database and retrieve sequences that are similar to a query sequence using a word-based method.
Word-based methods (for example BLAST, gapped BLAST, MEGABLAST, WU-BLAST etc.) are usually quicker than alignment-based methods. They may or may not handle gaps.
Sequence database search (by sequence using word-based methods)
Search a sequence database and retrieve sequences that are similar to a query sequence using a sequence profile-based method, or with a supplied profile as query.
Sequence database search (by sequence using profile-based methods)
Search a sequence database for sequences that are similar to a query sequence using a local alignment-based method.
This includes tools based on the Smith-Waterman algorithm or FASTA.
Sequence database search (by sequence using local alignment-based methods)
Search sequence(s) or a sequence database for sequences that are similar to a query sequence using a global alignment-based method.
This includes tools based on the Needleman and Wunsch algorithm.
Sequence database search (by sequence using global alignment-based methods)
Search a DNA database (for example a database of conserved sequence tags) for matches to Sequence-Tagged Site (STS) primer sequences.
STSs are genetic markers that are easily detected by the polymerase chain reaction (PCR) using specific primers.
Sequence database search (by sequence for primer sequences)
Search sequence(s) or a sequence database for sequences which match a set of peptide masses, for example a peptide mass fingerprint from mass spectrometry.
Sequence database search (by molecular weight)
Search sequence(s) or a sequence database for sequences of a given isoelectric point.
Sequence database search (by isoelectric point)
Query a tertiary structure database and retrieve entries with a given entry code or accession number.
Query a tertiary structure database and retrieve entries containing a given keyword.
Search a tertiary structure database and retrieve structures with a sequence similar to a query sequence.
Search a database of molecular structure and retrieve structures that are similar to a query structure.
Structure database search (by structure)
Annotate a molecular sequence record with terms from a controlled vocabulary.
Annotate a genome sequence with terms from a controlled vocabulary.
Generate the reverse and / or complement of a nucleotide sequence.
Nucleic acid sequence reverse and complement
Generate a random sequence, for example, with a specific character composition.
Generate digest fragments for a nucleotide sequence containing restriction sites.
This is often followed by calculation of protein fragment masses (http://edamontology.org/operation_0398).
Cleave a protein sequence into peptide fragments (corresponding to enzymatic or chemical cleavage).
Mutate a molecular sequence a specified amount or shuffle it to produce a randomised sequence with the same overall composition.
Mask characters in a molecular sequence (replacing those characters with a mask character).
For example, SNPs or repeats in a DNA sequence might be masked.
Cut (remove) characters or a region from a molecular sequence.
Create (or remove) restriction sites in sequences, for example using silent mutations.
Transcribe a nucleotide sequence into mRNA sequence(s).
Calculate base frequency or word composition of a nucleotide sequence.
Sequence composition calculation (nucleic acid)
Calculate amino acid frequency or word composition of a protein sequence.
Sequence composition calculation (protein)
Find (and possibly render) short repetitive subsequences (repeat sequences) in (typically nucleotide) sequences.
Analyse repeat sequence organisation such as periodicity.
Analyse the hydrophobic, hydrophilic or charge properties of a protein structure.
Protein hydropathy calculation (from structure)
Calculate solvent accessible or buried surface areas in protein or other molecular structures.
Protein solvent accessibility calculation
Solvent accessibility might be calculated for the backbone, sidechain and total (backbone plus sidechain).
Identify clusters of hydrophobic or charged residues in a protein structure.
Calculate whether a protein structure has an unusually large net charge (dipole moment).
Calculate the molecular surface area in proteins and other macromolecules.
Protein surface and interior calculation
Identify or predict catalytic residues, active sites or other ligand-binding sites in protein structures.
Protein binding site prediction (from structure)
Analyse the interaction of protein with nucleic acids, e.g. RNA or DNA-binding sites, interfaces etc.
Protein-nucleic acid binding site analysis
Protein-nucleic acid interaction analysis
Decompose a structure into compact or globular fragments (protein peeling).
Calculate a matrix of distance between residues (for example the C-alpha atoms) in a protein structure.
Calculate a residue contact map (typically all-versus-all inter-residue contacts) for a protein structure.
Calculate clusters of contacting residues in protein structures.
This includes for example clusters of hydrophobic or charged residues, or clusters of contacting residues which have a key structural or functional role.
Identify potential hydrogen bonds between amino acids and other groups.
The output might include the atoms involved in the bond, bond geometric parameters and bond enthalpy.
Calculate non-canonical atomic interactions in protein structures.
Residue non-canonical interaction detection
Calculate a Ramachandran plot of a protein structure.
Validate a Ramachandran plot of a protein structure.
Calculate the molecular weight of a protein sequence or fragments.
Predict extinction coefficients or optical density of a protein sequence.
Protein extinction coefficient calculation
Calculate pH-dependent properties from pKa calculations of a protein sequence.
Protein pH-dependent property calculation
Hydropathy calculation on a protein sequence.
Protein hydropathy calculation (from sequence)
Calculate isoelectric point of a protein sequence.
Estimate hydrogen exchange rate of a protein sequence.
Protein hydrogen exchange rate calculation
Calculate hydrophobic or hydrophilic / charged regions of a protein sequence.
Calculate aliphatic index (relative volume occupied by aliphatic side chains) of a protein.
Calculate the hydrophobic moment of a peptide sequence and recognize amphiphilicity.
Predict the stability or globularity of a protein sequence, whether it is intrinsically unfolded etc.
Predict the solubility or atomic solvation energy of a protein sequence.
Predict crystallizability of a protein sequence.
Detect or predict signal peptides (and typically predict subcellular localisation) of eukaryotic proteins.
Protein signal peptide detection (eukaryotes)
Detect or predict signal peptides (and typically predict subcellular localisation) of bacterial proteins.
Protein signal peptide detection (bacteria)
Predict MHC class I or class II binding peptides, promiscuous binding peptides, immunogenicity etc.
Predict, recognise and identify positional features in protein sequences such as functional sites or regions and secondary structure.
Methods typically involve scanning for known motifs, patterns and regular expressions.
Protein feature prediction (from sequence)
Predict, recognise and identify features in nucleotide sequences such as functional sites or regions, typically by scanning for known motifs, patterns and regular expressions.
Sequence feature detection (nucleic acid)
This is placeholder but does not comprehensively include all child concepts - please inspect other concepts under "Nucleic acid sequence analysis" for example "Gene prediction", for other feature detection operations.
Predict antigenic determinant sites (epitopes) in protein sequences.
Predict post-translation modification sites in protein sequences.
Post-translation modification site prediction
Post-translational modification analysis
Post-translational modification site prediction
Protein post-translation modification site prediction
N-terminal myristoylation site prediction
Methods might predict sites of methylation, N-terminal myristoylation, N-terminal acetylation, sumoylation, palmitoylation, phosphorylation, sulfation, glycosylation, glycosylphosphatidylinositol (GPI) modification sites (GPI lipid anchor signals) etc.
Detect or predict signal peptides and signal peptide cleavage sites in protein sequences.
Methods might use sequence motifs and features, amino acid composition, profiles, machine-learned classifiers, etc.
Predict catalytic residues, active sites or other ligand-binding sites in protein sequences.
Protein binding site prediction (from sequence)
Predict or detect RNA and DNA-binding binding sites in protein sequences.
Protein-nucleic acid binding site detection
Protein-nucleic acid binding site prediction
This includes methods that predict and optimise zinc finger protein domains for DNA/RNA binding (for example for transcription factors and nucleases).
Predict protein sites that are key to protein folding, such as possible sites of nucleation or stabilisation.
Detect or predict cleavage sites (enzymatic or chemical) in protein sequences.
Predict epitopes that bind to MHC class I molecules.
Predict epitopes that bind to MHC class II molecules.
Detect, predict and identify whole gene structure in DNA sequences. This includes protein coding regions, exon-intron structure, regulatory regions etc.
Detect, predict and identify genetic elements such as promoters, coding regions, splice sites, etc in DNA sequences.
Methods for gene prediction might be ab initio, based on phylogenetic comparisons, use motifs, sequence features, support vector machine, alignment etc.
Detect or predict transposons, retrotransposons / retrotransposition signatures etc.
Detect polyA signals in nucleotide sequences.
Detect quadruplex-forming motifs in nucleotide sequences.
Quadruplex (4-stranded) structures are formed by guanine-rich regions and are implicated in various important biological processes and as therapeutic targets.
Find CpG rich regions in a nucleotide sequence or isochores in genome sequences.
An isochore is long region (> 3 KB) of DNA with very uniform GC content, in contrast to the rest of the genome. Isochores tend tends to have more genes, higher local melting or denaturation temperatures, and different flexibility. Methods might calculate fractional GC content or variation of GC content, predict methylation status of CpG islands etc. This includes methods that visualise CpG rich regions in a nucleotide sequence, for example plot isochores in a genome sequence.
Find and identify restriction enzyme cleavage sites (restriction sites) in (typically) DNA sequences, for example to generate a restriction map.
Identify or predict nucleosome exclusion sequences (nucleosome free regions) in DNA.
Nucleosome exclusion sequence prediction
Nucleosome formation sequence prediction
Identify, predict or analyse splice sites in nucleotide sequences.
Methods might require a pre-mRNA or genomic DNA sequence.
Predict whole gene structure using a combination of multiple methods to achieve better predictions.
Find operons (operators, promoters and genes) in bacteria genes.
Predict protein-coding regions (CDS or exon) or open reading frames in nucleotide sequences.
Predict selenocysteine insertion sequence (SECIS) in a DNA sequence.
Selenocysteine insertion sequence (SECIS) prediction
SECIS elements are around 60 nucleotides in length with a stem-loop structure directs the cell to translate UGA codons as selenocysteines.
This includes comparative genomics approaches that identify common, conserved (homologous) or synonymous transcriptional regulatory elements. For example cross-species comparison of transcription factor binding sites (TFBS). Methods might analyse co-regulated or co-expressed genes, or sets of oppositely expressed genes.
Identify or predict transcriptional regulatory motifs, patterns, elements or regions in DNA sequences.
Transcription regulatory element prediction
Translational regulatory element prediction
This includes promoters, enhancers, silencers and boundary elements / insulators, regulatory protein or transcription factor binding sites etc. Methods might be specific to a particular genome and use motifs, word-based / grammatical methods, position-specific frequency matrices, discriminative pattern analysis etc.
Transcriptional regulatory element prediction
Predict translation initiation sites, possibly by searching a database of sites.
Identify or predict whole promoters or promoter elements (transcription start sites, RNA polymerase binding site, transcription factor binding sites, promoter enhancers etc) in DNA sequences.
Methods might recognize CG content, CpG islands, splice sites, polyA signals etc.
Identify, predict or analyse cis-regulatory elements in DNA sequences (TATA box, Pribnow box, SOS box, CAAT box, CCAAT box, operator etc.) or in RNA sequences (e.g. riboswitches).
Transcriptional regulatory element prediction (DNA-cis)
Transcriptional regulatory element prediction (RNA-cis)
Cis-regulatory elements (cis-elements) regulate the expression of genes located on the same strand from which the element was transcribed. Cis-elements are found in the 5' promoter region of the gene, in an intron, or in the 3' untranslated region. Cis-elements are often binding sites of one or more trans-acting factors. They also occur in RNA sequences, e.g. a riboswitch is a region of an mRNA molecule that bind a small target molecule that regulates the gene's activity.
Identify, predict or analyse cis-regulatory elements (for example riboswitches) in RNA sequences.
Identify or predict functional RNA sequences with a gene regulatory role (trans-regulatory elements) or targets.
Transcriptional regulatory element prediction (trans)
Trans-regulatory elements regulate genes distant from the gene from which they were transcribed.
Identify matrix/scaffold attachment regions (MARs/SARs) in DNA sequences.
Matrix/scaffold attachment site prediction
MAR/SAR sites often flank a gene or gene cluster and are found nearby cis-regulatory sequences. They might contribute to transcription regulation.
Identify or predict transcription factor binding sites in DNA sequences.
Transcription factor binding site prediction
Identify or predict exonic splicing enhancers (ESE) in exons.
An exonic splicing enhancer (ESE) is 6-base DNA sequence motif in an exon that enhances or directs splicing of pre-mRNA or hetero-nuclear RNA (hnRNA) into mRNA.
Evaluate molecular sequence alignment accuracy.
Evaluation might be purely sequence-based or use structural information.
Analyse character conservation in a molecular sequence alignment, for example to derive a consensus sequence.
Use this concept for methods that calculate substitution rates, estimate relative site variability, identify sites with biased properties, derive a consensus sequence, or identify highly conserved or very poorly conserved sites, regions, blocks etc.
Sequence alignment analysis (conservation)
Analyse correlations between sites in a molecular sequence alignment.
This is typically done to identify possible covarying positions and predict contacts or structural constraints in protein structures.
Sequence alignment analysis (site correlation)
Detects chimeric sequences (chimeras) from a sequence alignment.
A chimera includes regions from two or more phylogenetically distinct sequences. They are usually artifacts of PCR and are thought to occur when a prematurely terminated amplicon reanneals to another DNA strand and is subsequently copied to completion in later PCR cycles.
Detect recombination (hotspots and coldspots) and identify recombination breakpoints in a sequence alignment.
Sequence alignment analysis (recombination detection)
Tools might use a genetic algorithm, quartet-mapping, bootscanning, graphical methods, random forest model and so on.
Identify insertion, deletion and duplication events from a sequence alignment.
Sequence alignment analysis (indel detection)
Predict nucleosome formation potential of DNA sequences.
Nucleosome formation potential prediction
Calculate a thermodynamic property of DNA or DNA/RNA, such as melting temperature, enthalpy and entropy.
Nucleic acid thermodynamic property calculation
Calculate and plot a DNA or DNA/RNA melting profile.
A melting profile is used to visualise and analyse partly melted DNA conformations.
Calculate and plot a DNA or DNA/RNA stitch profile.
A stitch profile represents the alternative conformations that partly melted DNA can adopt in a temperature range.
Calculate and plot a DNA or DNA/RNA melting curve.
Calculate and plot a DNA or DNA/RNA probability profile.
Nucleic acid probability profile plotting
Calculate and plot a DNA or DNA/RNA temperature profile.
Nucleic acid temperature profile plotting
Calculate curvature and flexibility / stiffness of a nucleotide sequence.
Identify or predict microRNA sequences (miRNA) and precursors or microRNA targets / binding sites in a DNA sequence.
Identify or predict tRNA genes in genomic sequences (tRNA).
Assess binding specificity of putative siRNA sequence(s), for example for a functional assay, typically with respect to designing specific siRNA sequences.
Predict secondary structure of protein sequence(s) using multiple methods to achieve better predictions.
Protein secondary structure prediction (integrated)
Predict helical secondary structure of protein sequences.
Protein secondary structure prediction (helices)
Predict turn structure (for example beta hairpin turns) of protein sequences.
Protein secondary structure prediction (turns)
Predict open coils, non-regular secondary structure and intrinsically disordered / unstructured regions of protein sequences.
Protein secondary structure prediction (coils)
Predict cysteine bonding state and disulfide bond partners in protein sequences.
Not sustainable to have protein type-specific concepts.
Predict G protein-coupled receptors (GPCR).
Analyse G-protein coupled receptor proteins (GPCRs).
This includes methods that predict the folding pathway(s) or non-native structural intermediates of a protein.
Predict tertiary structure (backbone and side-chain conformation) of protein sequences.
Methods might identify thermodynamically stable or evolutionarily conserved structures.
Predict tertiary structure of protein sequence(s) without homologs of known structure.
Build a three-dimensional protein model based on known (for example homologs) structures.
The model might be of a whole, part or aspect of protein structure. Molecular modelling methods might use sequence-structure alignment, structural templates, molecular dynamics, energy minimisation etc.
Model the structure of a protein in complex with a small molecule or another macromolecule.
This includes protein-protein interactions, protein-nucleic acid, protein-ligand binding etc. Methods might predict whether the molecules are likely to bind in vivo, their conformation when bound, the strength of the interaction, possible mutations to achieve bonding and so on.
Methods might require a preliminary C(alpha) trace.
Scaffold selection, scaffold search, epitope grafting and design optimization are stages of backbone modelling done during rational vaccine design.
Model, analyse or edit amino acid side chain conformation in protein structure, optimize side-chain packing, hydrogen bonding etc.
Antibody optimisation is to optimize the antibody-interacting surface of the antigen (epitope). Antigen optimisation is to optimize the antigen-interacting surface of the antibody (paratope). Antigen resurfacing is to resurface the antigen by varying the sequence of non-epitope regions.
Methods might use a residue rotamer library.
This includes rotamer likelihood prediction: the prediction of rotamer likelihoods for all 20 amino acid types at each position in a protein structure, where output typically includes, for each residue position, the likelihoods for the 20 amino acid types with estimated reliability of the 20 likelihoods.
Model loop conformation in protein structures.
Model protein-ligand (for example protein-peptide) binding using comparative modelling or other techniques.
Methods aim to predict the position and orientation of a ligand bound to a protein receptor or enzyme.
Virtual screening is used in drug discovery to search libraries of small molecules in order to identify those molecules which are most likely to bind to a drug target (typically a protein receptor or enzyme).
Predict or optimise RNA sequences (sequence pools) with likely secondary and tertiary structure for in vitro selection.
Nucleic acid folding family identification
Structured RNA prediction and optimisation
Find single nucleotide polymorphisms (SNPs) - single nucleotide change in base positions - between sequences. Typically done for sequences from a high-throughput sequencing experiment that differ from a reference genome and which might, especially by reference to population frequency or functional data, indicate a polymorphism.
Single nucleotide polymorphism detection
This includes functional SNPs for large-scale genotyping purposes, disease-associated non-synonymous SNPs etc.
Generate a physical (radiation hybrid) map of genetic markers in a DNA sequence using provided radiation hybrid (RH) scores for one or more markers.
Map the genetic architecture of dynamic complex traits.
This can involve characterisation of the underlying quantitative trait loci (QTLs) or nucleotides (QTNs).
Infer haplotypes, either alleles at multiple loci that are transmitted together on the same chromosome, or a set of single nucleotide polymorphisms (SNPs) on a single chromatid that are statistically associated.
Haplotype inference can help in population genetic studies and the identification of complex disease genes, , and is typically based on aligned single nucleotide polymorphism (SNP) fragments. Haplotype comparison is a useful way to characterize the genetic variation between individuals. An individual's haplotype describes which nucleotide base occurs at each position for a set of common SNPs. Tools might use combinatorial functions (for example parsimony) or a likelihood function or model with optimisation such as minimum error correction (MEC) model, expectation-maximisation algorithm (EM), genetic algorithm or Markov chain Monte Carlo (MCMC).
Calculate linkage disequilibrium; the non-random association of alleles or polymorphisms at two or more loci (not necessarily on the same chromosome).
Linkage disequilibrium is identified where a combination of alleles (or genetic markers) occurs more or less frequently in a population than expected by chance formation of haplotypes.
Predict genetic code from analysis of codon usage data.
Render a representation of a distribution that consists of group of data points plotted on a simple scale.
Dot plots are useful when having not too many (e.g. 20) data points for each category. Example: draw a dotplot of sequence similarities identified from word-matching or character comparison.
Methods might perform one-to-one, one-to-many or many-to-many comparisons.
Align more than two molecular sequences.
This includes methods that use an existing alignment, for example to incorporate sequences into an alignment, or combine several multiple alignments into a single, improved alignment.
Locally align exactly two molecular sequences.
Local alignment methods identify regions of local similarity.
Pairwise sequence alignment generation (local)
Globally align exactly two molecular sequences.
Global alignment methods identify similarity across the entire length of the sequences.
Pairwise sequence alignment generation (global)
Locally align two or more molecular sequences.
Globally align two or more molecular sequences.
Align two or more molecular sequences with user-defined constraints.
Align two or more molecular sequences using multiple methods to achieve higher quality.
Align multiple sequences using relative gap costs calculated from neighbors in a supplied phylogenetic tree.
Multiple sequence alignment (phylogenetic tree-based)
Multiple sequence alignment construction (phylogenetic tree-based)
Phylogenetic tree-based multiple sequence alignment construction
Sequence alignment (phylogenetic tree-based)
Sequence alignment generation (phylogenetic tree-based)
This is supposed to give a more biologically meaningful alignment than standard alignments.
Align molecular secondary structure (represented as a 1D string).
Secondary structure alignment generation
Protein secondary structure alignment generation
RNA secondary structure alignment construction
RNA secondary structure alignment generation
Align (superimpose) exactly two molecular tertiary structures.
Align (superimpose) more than two molecular tertiary structures.
This includes methods that use an existing alignment.
Locally align (superimpose) exactly two molecular tertiary structures.
Local alignment methods identify regions of local similarity, common substructures etc.
Pairwise structure alignment generation (local)
Globally align (superimpose) exactly two molecular tertiary structures.
Global alignment methods identify similarity across the entire structures.
Pairwise structure alignment generation (global)
Locally align (superimpose) two or more molecular tertiary structures.
Globally align (superimpose) two or more molecular tertiary structures.
Sequence alignment generation (multiple profile)
Align exactly two molecular Structural (3D) profiles.
3D profile-to-3D profile alignment (pairwise)
Align two or more molecular 3D profiles.
Structural profile alignment generation (multiple)
Search and retrieve names of or documentation on bioinformatics tools, for example by keyword or which perform a particular function.
Search and retrieve names of or documentation on bioinformatics databases or query terms, for example by keyword.
Predict primers for large scale sequencing.
Predict primers for genotyping polymorphisms, for example single nucleotide polymorphisms (SNPs).
Predict primers for gene transcription profiling.
Predict primers that are conserved across multiple genomes or species.
Predict primers based on gene structure.
Sequence assembly by combining fragments using an existing backbone sequence, typically a reference genome.
The final sequence will resemble the backbone sequence. Mapping assemblers are usually much faster and less memory intensive than de-novo assemblers.
Sequence assembly by combining fragments without the aid of a reference sequence or genome.
De-novo assemblers are much slower and more memory intensive than mapping assemblers.
The process of assembling many short DNA sequences together such thay they represent the original chromosomes from which the DNA originated.
Sequence assembly for EST sequences (transcribed mRNA).
Assemblers must handle (or be complicated by) alternative splicing, trans-splicing, single-nucleotide polymorphism (SNP), recoding, and post-transcriptional modification.
Make sequence tag to gene assignments (tag mapping) of SAGE, MPSS and SBS data.
Sequence tag mapping assigns experimentally obtained sequence tags to known transcripts or annotate potential virtual sequence tags in a genome.
Process (read and / or write) serial analysis of gene expression (SAGE) data.
Process (read and / or write) massively parallel signature sequencing (MPSS) data.
Process (read and / or write) sequencing by synthesis (SBS) data.
Generate a heat map of expression data from e.g. microarray data.
The heat map usually uses a coloring scheme to represent expression values. They can show how quantitative measurements were influenced by experimental conditions.
Analyse one or more gene expression profiles, typically to interpret them in functional terms.
Map an expression profile to known biological pathways, for example, to identify or reconstruct a pathway.
Assign secondary structure from protein coordinate data.
Protein secondary structure assignment (from coordinate data)
Assign secondary structure from circular dichroism (CD) spectroscopic data.
Protein secondary structure assignment (from CD data)
Assign a protein tertiary structure (3D coordinates) from raw X-ray crystallography data.
Protein structure assignment (from X-ray crystallographic data)
Assign a protein tertiary structure (3D coordinates) from raw NMR spectroscopy data.
Protein structure assignment (from NMR data)
Construct a phylogenetic tree from a specific type of data.
Phylogenetic tree construction (data centric)
Phylogenetic tree generation (data centric)
Subconcepts of this concept reflect different types of data used to generate a tree, and provide an alternate axis for curation.
Construct a phylogenetic tree using a specific method.
Phylogenetic tree construction (method centric)
Phylogenetic tree generation (method centric)
Subconcepts of this concept reflect different computational methods used to generate a tree, and provide an alternate axis for curation.
Phylogenetic tree construction from molecular sequences.
Phylogenetic tree construction (from molecular sequences)
Phylogenetic tree generation (from molecular sequences)
Methods typically compare multiple molecular sequence and estimate evolutionary distances and relationships to infer gene families or make functional predictions.
Phylogenetic inference (from molecular sequences)
Phylogenetic tree construction from continuous quantitative character data.
Phylogenetic tree construction (from continuous quantitative characters)
Phylogenetic tree generation (from continuous quantitative characters)
Phylogenetic inference (from continuous quantitative characters)
Phylogenetic tree construction from gene frequency data.
Phylogenetic tree construction (from gene frequencies)
Phylogenetic tree generation (from gene frequencies)
Phylogenetic inference (from gene frequencies)
Phylogenetic tree construction from polymorphism data including microsatellites, RFLP (restriction fragment length polymorphisms), RAPD (random-amplified polymorphic DNA) and AFLP (amplified fragment length polymorphisms) data.
Phylogenetic tree construction (from polymorphism data)
Phylogenetic tree generation (from polymorphism data)
Phylogenetic inference (from polymorphism data)
Construct a phylogenetic species tree, for example, from a genome-wide sequence comparison.
Construct a phylogenetic tree by computing a sequence alignment and searching for the tree with the fewest number of character-state changes from the alignment.
Phylogenetic tree construction (parsimony methods)
Phylogenetic tree generation (parsimony methods)
This includes evolutionary parsimony (invariants) methods.
Phylogenetic inference (parsimony methods)
Construct a phylogenetic tree by computing (or using precomputed) distances between sequences and searching for the tree with minimal discrepancies between pairwise distances.
Phylogenetic tree construction (minimum distance methods)
Phylogenetic tree generation (minimum distance methods)
This includes neighbor joining (NJ) clustering method.
Phylogenetic inference (minimum distance methods)
Construct a phylogenetic tree by relating sequence data to a hypothetical tree topology using a model of sequence evolution.
Phylogenetic tree construction (maximum likelihood and Bayesian methods)
Phylogenetic tree generation (maximum likelihood and Bayesian methods)
Maximum likelihood methods search for a tree that maximizes a likelihood function, i.e. that is most likely given the data and model. Bayesian analysis estimate the probability of tree for branch lengths and topology, typically using a Monte Carlo algorithm.
Phylogenetic inference (maximum likelihood and Bayesian methods)
Construct a phylogenetic tree by computing four-taxon trees (4-trees) and searching for the phylogeny that matches most closely.
Phylogenetic tree construction (quartet methods)
Phylogenetic tree generation (quartet methods)
Phylogenetic inference (quartet methods)
Construct a phylogenetic tree by using artificial-intelligence methods, for example genetic algorithms.
Phylogenetic tree construction (AI methods)
Phylogenetic tree generation (AI methods)
Identify a plausible model of DNA substitution that explains a molecular (DNA or protein) sequence alignment.
Analyse the shape (topology) of a phylogenetic tree.
Apply bootstrapping or other measures to estimate confidence of a phylogenetic tree.
Construct a "gene tree" which represents the evolutionary history of the genes included in the study. This can be used to predict families of genes and gene function based on their position in a phylogenetic tree.
Phylogenetic tree analysis (gene family prediction)
Gene trees can provide evidence for gene duplication events, as well as speciation events. Where sequences from different homologs are included in a gene tree, subsequent clustering of the orthologs can demonstrate evolutionary history of the orthologs.
Analyse a phylogenetic tree to identify allele frequency distribution and change that is subject to evolutionary pressures (natural selection, genetic drift, mutation and gene flow). Identify type of natural selection (such as stabilizing, balancing or disruptive).
Phylogenetic tree analysis (natural selection)
Stabilizing/purifying (directional) selection favors a single phenotype and tends to decrease genetic diversity as a population stabilizes on a particular trait, selecting out trait extremes or deleterious mutations. In contrast, balancing selection maintain genetic polymorphisms (or multiple alleles), whereas disruptive (or diversifying) selection favors individuals at both extremes of a trait.
Compare two or more phylogenetic trees to produce a consensus tree.
Phylogenetic tree construction (consensus)
Phylogenetic tree generation (consensus)
Methods typically test for topological similarity between trees using for example a congruence index.
Compare two or more phylogenetic trees to detect subtrees or supertrees.
Phylogenetic sub/super tree construction
Compare two or more phylogenetic trees to calculate distances between trees.
Annotate a phylogenetic tree with terms from a controlled vocabulary.
Predict and optimise peptide ligands that elicit an immunological response.
Predict or optimise DNA to elicit (via DNA vaccination) an immunological response.
Reformat (a file or other report of) molecular sequence(s).
Reformat (a file or other report of) molecular sequence alignment(s).
Visualise, format or render a molecular sequence or sequences such as a sequence alignment, possibly with sequence features or properties shown.
Visualise, format or print a molecular sequence alignment.
Visualise, format or render sequence clusters.
Render or visualise a phylogenetic tree.
Visualise RNA secondary structure, knots, pseudoknots etc.
Render and visualise protein secondary structure.
Protein secondary structure visualisation
Visualise or render molecular 3D structure, for example a high-quality static picture or animation.
This includes visualisation of protein secondary structure such as knots, pseudoknots etc. as well as tertiary and quaternary structure.
Visualise microarray or other expression data.
Identify and analyse networks of protein interactions.
Protein interaction network visualisation
Draw or visualise restriction maps in DNA sequences.
Draw a circular maps of DNA, for example a plasmid map.
Identify folding families of related RNAs.
Compute energies of nucleic acid folding, e.g. minimum folding energies for DNA or RNA sequences or energy landscape of RNA mutants.
Retrieve existing annotation (or documentation), typically annotation on a database entity.
Use this concepts for tools which retrieve pre-existing annotations, not for example prediction methods that might make annotations.
Predict the biological or biochemical role of a protein, or other aspects of a protein function.
For functional properties that can be mapped to a sequence, use 'Sequence feature detection (protein)' instead.
Compare the functional properties of two or more proteins.
Submit a molecular sequence to a database.
Analyse a known network of gene regulation.
Parse, prepare or load a user-specified data file so that it is available for use.
Query a sequence data resource (typically a database) and retrieve sequences and / or annotation.
This includes direct retrieval methods (e.g. the dbfetch program) but not those that perform calculations on the sequence.
Query a tertiary structure data resource (typically a database) and retrieve structures, structure-related data and annotation.
This includes direct retrieval methods but not those that perform calculations on the sequence or structure.
Calculate the positions of dots that are homogeneously distributed over the surface of a molecule.
A dot has three coordinates (x,y,z) and (typically) a color.
Calculate the solvent accessibility ('accessible surface') for each atom in a structure.
Protein atom surface calculation (accessible)
Calculate the solvent accessibility ('accessible molecular surface') for each atom in a structure.
Protein atom surface calculation (accessible molecular)
Calculate the solvent accessibility ('accessible surface') for each residue in a structure.
Protein residue surface calculation (accessible)
Calculate the solvent accessibility ('vacuum accessible surface') for each residue in a structure. This is the accessibility of the residue when taken out of the protein together with the backbone atoms of any residue it is covalently bound to.
Protein residue surface calculation (vacuum accessible)
Calculate the solvent accessibility ('accessible molecular surface') for each residue in a structure.
Protein residue surface calculation (accessible molecular)
Calculate the solvent accessibility ('vacuum molecular surface') for each residue in a structure. This is the accessibility of the residue when taken out of the protein together with the backbone atoms of any residue it is covalently bound to.
Protein residue surface calculation (vacuum molecular)
Calculate the solvent accessibility ('accessible molecular surface') for a structure as a whole.
Protein surface calculation (accessible molecular)
Calculate the solvent accessibility ('accessible surface') for a structure as a whole.
Protein surface calculation (accessible)
Calculate for each residue in a protein structure all its backbone torsion angles.
Calculate for each residue in a protein structure all its torsion angles.
Calculate for each cysteine (bridge) all its torsion angles.
For each amino acid in a protein structure calculate the backbone angle tau.
Tau is the backbone angle N-Calpha-C (angle over the C-alpha).
Detect cysteine bridges (from coordinate data) in a protein structure.
Detect free cysteines in a protein structure.
A free cysteine is neither involved in a cysteine bridge, nor functions as a ligand to a metal.
Detect cysteines that are bound to metal in a protein structure.
Calculate protein residue contacts with nucleic acids in a structure.
Residue contact calculation (residue-nucleic acid)
Calculate protein residue contacts with metal in a structure.
Calculate ion contacts in a structure (all ions for all side chain atoms).
Residue contact calculation (residue-negative ion)
Detect 'bumps' between residues in a structure, i.e. those with pairs of atoms whose Van der Waals' radii interpenetrate more than a defined distance.
Calculate the number of symmetry contacts made by residues in a protein structure.
A symmetry contact is a contact between two atoms in different asymmetric unit.
Calculate contacts between residues and ligands in a protein structure.
Residue contact calculation (residue-ligand)
Calculate (and possibly score) salt bridges in a protein structure.
Salt bridges are interactions between oppositely charged atoms in different residues. The output might include the inter-atomic distance.
Predict rotamer likelihoods for all 20 amino acid types at each position in a protein structure.
Output typically includes, for each residue position, the likelihoods for the 20 amino acid types with estimated reliability of the 20 likelihoods.
Calculate for each position in a protein structure the chance that a proline, when introduced at this position, would increase the stability of the whole protein.
Identify poorly packed residues in protein structures.
Validate protein geometry, for example bond lengths, bond angles, torsion angles, chiralities, planaraties etc. An example is validation of a Ramachandran plot of a protein structure.
Extract a molecular sequence from a PDB file.
A HET group usually corresponds to ligands, lipids, but might also (not consistently) include groups that are attached to amino acids. Each HET group is supposed to have a unique three letter code and a unique name which might be given in the output.
Determine for residue the DSSP determined secondary structure in three-state (HSC).
Reformat (a file or other report of) tertiary structure data.
Assign cysteine bonding state and disulfide bond partners in protein structures.
Protein cysteine and disulfide bond assignment
Identify poor quality amino acid positions in protein structures.
Query a tertiary structure database and retrieve water molecules.
Identify or predict siRNA duplexes in RNA.
Process an EMBOSS listfile (list of EMBOSS Uniform Sequence Addresses).
Perform basic (non-analytical) operations on a report or file of sequences (which might include features), such as file concatenation, removal or ordering of sequences, creation of subset or a new file of sequences.
Perform basic (non-analytical) operations on a sequence alignment file, such as copying or removal and ordering of sequences.
Process (read and / or write) physicochemical property data for small molecules.
Search and retrieve documentation on a bioinformatics ontology.
Query an ontology and retrieve concepts or relations.
Identify a representative sequence from a set of sequences, typically using scores from pair-wise alignment or other comparison of the sequences.
Perform basic (non-analytical) operations on a file of molecular tertiary structural data.
Query a profile data resource and retrieve one or more profile(s) and / or associated annotation.
This includes direct retrieval methods that retrieve a profile by, e.g. the profile name.
Perform a statistical data operation of some type, e.g. calibration or validation.
Calculate a 3D-1D scoring matrix from analysis of protein sequence and structural data.
A 3D-1D scoring matrix scores the probability of amino acids occurring in different structural environments.
Visualise transmembrane proteins, typically the transmembrane regions within a sequence.
An operation performing purely illustrative (pedagogical) purposes.
Query a biological pathways database and retrieve annotation on one or more pathways.
Query a database and retrieve one or more data identifiers.
Calculate a density plot (of base composition) for a nucleotide sequence.
Analyse one or more known molecular sequences.
Process (read and / or write) protein interaction data.
Process (read and / or write) annotation of some type, typically annotation on an entry from a biological or biomedical database entity.
Analyse features in molecular sequences.
Basic (non-analytical) operations of some data, either a file or equivalent entity in memory, such that the same basic type of data is consumed as input and generated as output.
Analyse gene expression and regulation data.
Process (read and / or write) one or more structural (3D) profile(s) or template(s) of some type.
Process (read and / or write) an index of (typically a file of) biological data.
Process (read and / or write) some type of sequence profile.
Analyse protein function, typically by processing protein sequence and/or structural data, and generate an informative report.
Analyse, simulate or predict protein folding, typically by processing sequence and / or structural data. For example, predict sites of nucleation or stabilisation key to protein folding.
Analyse protein secondary structure data.
Process (read and / or write) data on the physicochemical property of a molecule.
Physicochemical property data processing
Predict oligonucleotide primers or probes.
Process (read and / or write) data of a specific type, for example applying analytical methods.
Search a database (or other data resource) with a supplied query and retrieve entries (or parts of entries) that are similar to the query.
Typically the query is compared to each entry and high scoring matches (hits) are returned. For example, a BLAST search of a sequence database.
Retrieve an entry (or part of an entry) from a data resource that matches a supplied query. This might include some primary data and annotation. The query is a data identifier or other indexed term. For example, retrieve a sequence record with the specified accession number, or matching supplied keywords.
Predict, recognise, detect or identify some properties of a biomolecule.
Compare two or more things to identify similarities.
Model or simulate some biological entity or system, typically using mathematical techniques including dynamical systems, statistical models, differential equations, and game theoretic models.
Perform basic operations on some data or a database.
Map properties to positions on an biological entity (typically a molecular sequence or structure), or assemble such an entity from constituent parts.
Design a biological entity (typically a molecular sequence or structure) with specific properties.
Process (read and / or write) microarray data.
Process (read and / or write) a codon usage table.
Retrieve a codon usage table and / or associated annotation.
Process (read and / or write) a gene expression profile.
Analyse gene expression patterns to identify sets of genes that are associated with a specific trait, condition, clinical outcome etc.
Gene sets can be defined beforehand by biological function, chromosome locations and so on.
Identify classes of genes or proteins that are over or under-represented in a large set of genes or proteins. For example analysis of a set of genes corresponding to a gene expression profile, annotated with Gene Ontology (GO) concepts, where eventual over-/under-representation of certain GO concept within the studied set of genes is revealed.
"Gene set analysis" (often used interchangeably or in an overlapping sense with "gene-set enrichment analysis") refers to the functional analysis (term enrichment) of a differentially expressed set of genes, rather than all genes analysed.
The Gene Ontology (GO) is typically used, the input is a set of Gene IDs, and the output of the analysis is typically a ranked list of GO concepts, each associated with a p-value.
Generate, analyse or handle a biological pathway or network.
Process (read and / or write) RNA secondary structure data.
Process (read and / or write) RNA tertiary structure data.
Generate, process or analyse phylogenetic tree or trees.
Process (read and / or write) protein secondary structure data.
Process (read and / or write) a network of protein interactions.
Process (read and / or write) one or more molecular sequences and associated annotation.
Process (read and / or write) a protein sequence and associated annotation.
Process (read and / or write) a nucleotide sequence and associated annotation.
Compare two or more molecular sequences.
Process (read and / or write) a sequence cluster.
Process (read and / or write) a sequence feature table.
Includes methods that predict whole gene structure using a combination of multiple methods to achieve better predictions.
Detect, predict and identify genes or components of genes in DNA sequences, including promoters, coding regions, splice sites, etc.
Classify G-protein coupled receptors (GPCRs) into families and subfamilies.
Predict G-protein coupled receptor (GPCR) coupling selectivity.
Process (read and / or write) a protein tertiary structure.
Calculate the solvent accessibility for each atom in a structure.
Calculate the solvent accessibility for each residue in a structure.
Calculate the solvent accessibility of a structure as a whole.
Process (read and / or write) a molecular sequence alignment.
Identify or predict protein-protein binding sites.
Process (read and / or write) a molecular tertiary structure.
Annotate a DNA map of some type with terms from a controlled vocabulary.
Retrieve a phylogenetic tree from a data resource.
Retrieve information on a protein interaction.
Data retrieval (protein interaction annotation)
Retrieve information on a protein family.
Data retrieval (protein family annotation)
Retrieve information on a specific gene.
Retrieve information on a specific genotype or phenotype.
Data retrieval (genotype and phenotype annotation)
Compare the architecture of two or more protein structures.
Identify the architecture of a protein structure.
Includes methods that try to suggest the most likely biological unit for a given protein X-ray crystal structure based on crystal symmetry and scoring of putative protein-protein interfaces.
The simulation of molecular (typically protein) conformation using a computational model of physical forces and computer simulation.
Analyse a nucleic acid sequence (using methods that are only applicable to nucleic acid sequences).
Nucleic acid sequence alignment analysis
Sequence alignment analysis (nucleic acid)
Analyse a protein sequence (using methods that are only applicable to protein sequences).
Analyse known molecular tertiary structures.
Analyse nucleic acid tertiary structural data.
Process (read and / or write) a molecular secondary structure.
Compare two or more molecular tertiary structures.
Render a helical wheel representation of protein secondary structure.
Render a topology diagram of protein secondary structure.
Methods might identify structural neighbors, find structural similarities or define a structural core.
Secondary structure comparison (protein)
Predict the subcellular localisation of a protein sequence.
Protein cellular localization prediction
Protein subcellular localisation prediction
The prediction might include subcellular localisation (nuclear, cytoplasmic, mitochondrial, chloroplast, plastid, membrane etc) or export (extracellular proteins) of a protein.
Calculate contacts between residues in a protein structure.
Residue contact calculation (residue-residue)
Identify potential hydrogen bonds between amino acid residues.
Hydrogen bond calculation (inter-residue)
Predict the interactions of proteins with other proteins.
Process (read and / or write) codon usage data.
Metagenomic inference is the profiling of phylogenetic marker genes in order to predict metagenome function.
Process (read and/or write) expression data from experiments measuring molecules (e.g. omics data), including analysis of one or more expression profiles, typically to interpret them in functional terms.
Process (read and / or write) a network of gene regulation.
Generate, process or analyse a biological pathway or network.
Analyse SAGE, MPSS or SBS experimental data, typically to identify or quantify mRNA transcripts.
Sequencing-based expression profile data analysis
Predict, analyse, characterize or model splice sites, splicing events and so on, typically by comparing multiple nucleic acid sequences.
Process (read and / or write) nucleic acid sequence or structural data.
Process (read and / or write) protein sequence or structural data.
Process (read and / or write) molecular sequence data.
Process (read and / or write) molecular structural data.
Analyse a protein sequence alignment, typically to detect features or make predictions.
Compare two or more nucleic acid sequences.
Back-translate a protein sequence into DNA.
Edit or change a nucleic acid sequence, either randomly or specifically.
Edit or change a protein sequence, either randomly or specifically.
Generate a nucleic acid sequence by some means.
Generate a protein sequence by some means.
Visualise, format or render a nucleic acid sequence.
Various nucleic acid sequence analysis methods might generate a sequence rendering but are not (for brevity) listed under here.
Visualise, format or render a protein sequence.
Various protein sequence analysis methods might generate a sequence rendering but are not (for brevity) listed under here.
Compare nucleic acid tertiary structures.
Process (read and / or write) nucleic acid tertiary structure data.
Generate a map of a DNA sequence annotated with positional or non-positional features of some type.
Process (read and / or write) a DNA map of some type.
Analyse the hydrophobic, hydrophilic or charge properties of a protein (from analysis of sequence or structural information).
Identify or predict catalytic residues, active sites or other ligand-binding sites in protein sequences or structures.
Build clusters of similar structures, typically using scores from structural alignment methods.
Generate a physical DNA map (sequence map) from analysis of sequence tagged sites (STS).
An STS is a short subsequence of known sequence and location that occurs only once in the chromosome or genome that is being mapped. Sources of STSs include 1. expressed sequence tags (ESTs), simple sequence length polymorphisms (SSLPs), and random genomic sequences from cloned genomic DNA or database sequences.
Compare two or more entities, typically the sequence or structure (or derivatives) of macromolecules, to identify equivalent subunits.
Calculate the molecular weight of a protein (or fragments) and compare it to another protein or reference data. Generally used for protein identification.
Compare the physicochemical properties of two or more proteins (or reference data).
Compare two or more molecular secondary structures.
Generate a Hopp and Woods plot of antigenicity of a protein.
Generate a view of clustered quantitative data, annotated with textual information.
In the case of microarray data, visualise clustered gene expression data as a set of profiles, where each profile shows the gene expression values of a cluster across samples on the X-axis.
Visualise clustered quantitative data as set of different profiles, where each profile is plotted versus different entities or samples on the X-axis.
Microarray cluster temporal graph rendering
Generate a dendrograph of raw, preprocessed or clustered expression (e.g. microarray) data.
Generate a plot of distances (distance or correlation matrix) between expression values.
Visualise clustered expression data using a tree diagram.
Expression data tree or dendrogram rendering
Examples for visualization are the distribution of variance over the components, loading and score plots.
Visualize the results of a principal component analysis (orthogonal data transformation). For example, visualization of the principal components (essential subspace) coming from a Principal Component Analysis (PCA) on the trajectory atomistic coordinates of a molecular structure.
Microarray principal component rendering
The use of Principal Component Analysis (PCA), a multivariate statistical analysis to obtain collective variables on the atomic positional fluctuations, helps to separate the configurational space in two subspaces: an essential subspace containing relevant motions, and another one containing irrelevant local fluctuations.
Comparison of two sets of quantitative data such as two samples of gene expression values.
Render a graph in which the values of two variables are plotted along two axes; the pattern of the points reveals any correlation.
Visualise gene expression data where each band (or line graph) corresponds to a sample.
Visualise gene expression data after hierarchical clustering for representing hierarchical relationships.
In the case of micorarray data, visualise raw and pre-processed gene expression data, via a plot showing over- and under-expression along with mean, upper and lower quartiles.
Generate a box plot, i.e. a depiction of groups of numerical data through their quartiles.
Generate a physical (sequence) map of a DNA sequence showing the physical distance (base pairs) between features or landmarks such as restriction sites, cloned DNA fragments, genes and other genetic markers.
Apply analytical methods to existing data of a specific type.
This excludes non-analytical methods that read and write the same basic type of data (for that, see 'Data handling').
Process or analyse an alignment of molecular sequences or structures.
Analyse a body of scientific text (typically a full text article from a scientific journal.)
Analyse the interactions of two or more molecules (or parts of molecules) that are known to interact.
Includes analysis of raw experimental protein-protein interaction data from for example yeast two-hybrid analysis, protein microarrays, immunoaffinity chromatography followed by mass spectrometry, phage display etc.
Analyse the interactions of proteins with other proteins.
Calculate contacts between residues, or between residues and other groups, in a protein structure, on the basis of distance calculations.
Residue contact calculation (residue-metal)
This includes identifying HET groups, which usually correspond to ligands, lipids, but might also (not consistently) include groups that are attached to amino acids. Each HET group is supposed to have a unique three letter code and a unique name which might be given in the output. It can also include calculation of symmetry contacts, i.e. a contact between two atoms in different asymmetric unit.
Process (read and / or write) an alignment of two or more molecular sequences, structures or derived data.
Process (read and / or write) a molecular tertiary (3D) structure alignment.
Calculate codon usage bias, e.g. generate a codon usage bias plot.
Calculate the differences in codon usage fractions between two sequences, sets of sequences, codon usage tables etc.
Assign molecular sequences, structures or other biological data to a specific group or category according to qualities it shares with that group or category.
Process (read and / or write) molecular interaction data.
Assign molecular sequence(s) to a group or category.
Assign molecular structure(s) to a group or category.
Compare two or more proteins (or some aspect) to identify similarities.
Compare two or more nucleic acids to identify similarities.
Predict, recognise, detect or identify some properties of proteins.
Predict, recognise, detect or identify some properties of nucleic acids.
Prediction and recognition (nucleic acid)
Edit, convert or otherwise change a molecular tertiary structure, either randomly or specifically.
Edit, convert or otherwise change a molecular sequence alignment, either randomly or specifically.
Render (visualise) a biological pathway or network.
Predict general (non-positional) functional properties of a protein from analysing its sequence.
For functional properties that are positional, use 'Protein site detection' instead.
Protein function prediction (from sequence)
(jison)This is a distinction made on basis of input; all features exist can be mapped to a sequence so this isn't needed (consolidate with "Protein feature detection").
Predict, recognise and identify functional or other key sites within protein sequences, typically by scanning for known motifs, patterns and regular expressions.
Calculate (or predict) physical or chemical properties of a protein, including any non-positional properties of the molecular sequence, from processing a protein sequence.
Predict, recognise and identify positional features in proteins from analysing protein structure.
Protein feature prediction (from structure)
Predict, recognise and identify positional features in proteins from analysing protein sequences or structures.
Features includes functional sites or regions, secondary structure, structural domains and so on. Methods might use fingerprints, motifs, profiles, hidden Markov models, sequence alignment etc to provide a mapping of a query protein sequence to a discriminatory element. This includes methods that search a secondary protein database (Prosite, Blocks, ProDom, Prints, Pfam etc.) to assign a protein sequence(s) to a known protein family or group.
Screen a molecular sequence(s) against a database (of some type) to identify similarities between the sequence and database entries.
Predict a network of protein interactions.
Design (or predict) nucleic acid sequences with specific chemical or physical properties.
Edit a data entity, either randomly or specifically.
Evaluate a DNA sequence assembly, typically for purposes of quality control.
Align two or more (tpyically huge) molecular sequences that represent genomes.
Reconstruction of a sequence assembly in a localised area.
Render and visualise a DNA sequence assembly.
Identify base (nucleobase) sequence from a fluorescence 'trace' data generated by an automated DNA sequencer.
The mapping of methylation sites in a DNA (genome) sequence. Typically, the mapping of high-throughput bisulfite reads to the reference genome.
Bisulfite mapping follows high-throughput sequencing of DNA which has undergone bisulfite treatment followed by PCR amplification; unmethylated cytosines are specifically converted to thymine, allowing the methylation status of cytosine in the DNA to be detected.
Identify and filter a (typically large) sequence data set to remove sequences from contaminants in the sample that was sequenced.
Trim sequences (typically from an automated DNA sequencer) to remove misleading ends.
For example trim polyA tails, introns and primer sequence flanking the sequence of amplified exons, or other unwanted sequence.
Trim sequences (typically from an automated DNA sequencer) to remove sequence-specific end regions, typically contamination from vector sequences.
Trim sequences (typically from an automated DNA sequencer) to remove the sequence ends that extend beyond an assembled reference sequence.
Cut (remove) the end from a molecular sequence.
This includes ennd trimming Trim sequences (typically from an automated DNA sequencer) to remove misleading ends. For example trim polyA tails, introns and primer sequence flanking the sequence of amplified exons, or other unwanted sequence. trimming to a reference sequence, Trim sequences (typically from an automated DNA sequencer) to remove the sequence ends that extend beyond an assembled reference sequence. vector trimming Trim sequences (typically from an automated DNA sequencer) to remove sequence-specific end regions, typically contamination from vector sequences.
Compare the features of two genome sequences.
Genomic elements that might be compared include genes, indels, single nucleotide polymorphisms (SNPs), retrotransposons, tandem repeats and so on.
Detect errors in DNA sequences generated from sequencing projects).
Analyse DNA sequence data to identify differences between the genetic composition (genotype) of an individual compared to other individual's or a reference sequence.
Methods might consider cytogenetic analyses, copy number polymorphism (and calculate copy number calls for copy-number variation(CNV) regions), single nucleotide polymorphism (SNP), , rare copy number variation (CNV) identification, loss of heterozygosity data and so on.
Analyse a genetic variation, for example to annotate its location, alleles, classification, and effects on individual transcripts predicted for a gene model.
Genetic variation annotation provides contextual interpretation of coding SNP consequences in transcripts. It allows comparisons to be made between variation data in different populations or strains for the same transcript.
Align short oligonucleotide sequences (reads) to a larger (genomic) sequence.
The purpose of read mapping is to identify the location of sequenced fragments within a reference genome and assumes that there is, in fact, at least local similarity between the fragment and reference sequences.
A varient of oligonucleotide mapping where a read is mapped to two separate locations because of possible structural variation.
Analyse DNA sequences in order to identify a DNA 'barcode'; marker genes or any short fragment(s) of DNA that are useful to diagnose the taxa of biological organisms.
Identify single nucleotide change in base positions in sequencing data that differ from a reference genome and which might, especially by reference to population frequency or functional data, indicate a polymorphism.
"Polymorphism detection" and "Variant calling" are essentially the same thing - keeping the later as a more prevalent term nowadays.
Detect mutations in multiple DNA sequences, for example, from the alignment and comparison of the fluorescent traces produced by DNA sequencing hardware.
Visualise, format or render an image of a Chromatogram.
Analyse cytosine methylation states in nucleic acid sequences.
Determine cytosine methylation status of specific positions in a nucleic acid sequences.
Measure the overall level of methyl cytosines in a genome from analysis of experimental data, typically from chromatographic methods and methyl accepting capacity assay.
Analysing the DNA methylation of specific genes or regions of interest.
Methylation level analysis (gene-specific)
Visualise, format or render a nucleic acid sequence that is part of (and in context of) a complete genome sequence.
Compare the sequence or features of two or more genomes, for example, to find matching regions.
Many sequence alignment tasks involving many or very large sequences rely on a precomputed index of the sequence to accelerate the alignment. The Burrows-Wheeler Transform (BWT) is a permutation of the genome based on a suffix array algorithm. A suffix array consists of the lexicographically sorted list of suffixes of a genome.
Generate an index of a genome sequence using the Burrows-Wheeler algorithm.
The Burrows-Wheeler Transform (BWT) is a permutation of the genome based on a suffix array algorithm.
Generate an index of a genome sequence using a suffix arrays algorithm.
A suffix array consists of the lexicographically sorted list of suffixes of a genome.
Analyse one or more spectra from mass spectrometry (or other) experiments.
Identify peaks in a spectrum from a mass spectrometry, NMR, or some other spectrum-generating experiment.
Link together a non-contiguous series of genomic sequences into a scaffold, consisting of sequences separated by gaps of known length. The sequences that are linked are typically typically contigs; contiguous sequences corresponding to read overlaps.
Scaffold may be positioned along a chromosome physical map to create a "golden path".
Fill the gaps in a sequence assembly (scaffold) by merging in additional sequences.
Different techniques are used to generate gap sequences to connect contigs, depending on the size of the gap. For small (5-20kb) gaps, PCR amplification and sequencing is used. For large (>20kb) gaps, fragments are cloned (e.g. in BAC (Bacterial artificial chromosomes) vectors) and then sequenced.
Analyse raw sequence data from a sequencing pipeline and identify (and possiby fix) problems.
Pre-process sequence reads to ensure (or improve) quality and reliability.
For example process paired end reads to trim low quality ends remove short sequences, identify sequence inserts, detect chimeric reads, or remove low quality sequnces including vector, adaptor, low complexity and contaminant sequences. Sequences might come from genomic DNA library, EST libraries, SSH library and so on.
Estimate the frequencies of different species from analysis of the molecular sequences, typically of DNA recovered from environmental samples.
Identify putative protein-binding regions in a genome sequence from analysis of Chip-sequencing data or ChIP-on-chip data.
Chip-sequencing combines chromatin immunoprecipitation (ChIP) with massively parallel DNA sequencing to generate a set of reads, which are aligned to a genome sequence. The enriched areas contain the binding sites of DNA-associated proteins. For example, a transcription factor binding site. ChIP-on-chip in contrast combines chromatin immunoprecipitation ('ChIP') with microarray ('chip'). "Peak-pair calling" is similar to "Peak calling" in the context of ChIP-exo.
Identify from molecular sequence analysis (typically from analysis of microarray or RNA-seq data) genes whose expression levels are significantly different between two sample groups.
Differentially expressed gene identification
Differential gene expression analysis is used, for example, to identify which genes are up-regulated (increased expression) or down-regulated (decreased expression) between a group treated with a drug and a control groups.
Analyse gene expression patterns (typically from DNA microarray datasets) to identify sets of genes that are associated with a specific trait, condition, clinical outcome etc.
Classify variants based on their potential effect on genes, especially functional effects on the expressed proteins.
Variants are typically classified by their position (intronic, exonic, etc.) in a gene transcript and (for variants in coding exons) by their effect on the protein sequence (synonymous, non-synonymous, frameshifting, etc.)
Identify biologically interesting variants by prioritizing individual variants, for example, homozygous variants absent in control genomes.
Variant prioritisation can be used for example to produce a list of variants responsible for 'knocking out' genes in specific genomes. Methods amino acid substitution, aggregative approaches, probabilistic approach, inheritance and unified likelihood-frameworks.
Detect, identify and map mutations, such as single nucleotide polymorphisms, short indels and structural variants, in multiple DNA sequences. Typically the alignment and comparison of the fluorescent traces produced by DNA sequencing hardware, to study genomic alterations.
Methods often utilise a database of aligned reads.
Somatic variant calling is the detection of variations established in somatic cells and hence not inherited as a germ line variant.
Detect large regions in a genome subject to copy-number variation, or other structural variations in genome(s).
Methods might involve analysis of whole-genome array comparative genome hybridisation or single-nucleotide polymorphism arrays, paired-end mapping of sequencing data, or from analysis of short reads from new sequencing technologies.
Analyse sequencing data from experiments aiming to selectively sequence the coding regions of the genome.
Analyse mapping density (read depth) of (typically) short reads from sequencing platforms, for example, to detect deletions and duplications.
Combine classical quantitative trait loci (QTL) analysis with gene expression profiling, for example, to describe describe cis- and trans-controlling elements for the expression of phenotype associated genes.
Gene expression quantitative trait loci profiling
Estimate the number of copies of loci of particular gene(s) in DNA sequences typically from gene-expression profiling technology based on microarray hybridisation-based experiments. For example, estimate copy number (or marker dosage) of a dominant marker in samples from polyploid plant cells or tissues, or chromosomal gains and losses in tumors.
Methods typically implement some statistical model for hypothesis testing, and methods estimate total copy number, i.e. do not distinguish the two inherited chromosomes quantities (specific copy number).
Remove forward and/or reverse primers from nucleic acid sequences (typically PCR products).
Infer a transcriptome sequence by analysis of short sequence reads.
Infer a transcriptome sequence without the aid of a reference genome, i.e. by comparing short sequences (reads) to each other.
Infer a transcriptome sequence by mapping short reads to a reference genome.
Convert one set of sequence coordinates to another, e.g. convert coordinates of one assembly to another, cDNA to genomic, CDS to genomic, protein translation to genomic etc.
Calculate similarity between 2 or more documents.
Cluster (group) documents on the basis of their calculated similarity.
Recognise named entities, ontology concepts, tags, events, and dictionary terms within documents.
Map data identifiers to one another for example to establish a link between two biological databases for the purposes of data integration.
The mapping can be achieved by comparing identifier values or some other means, e.g. exact matches to a provided sequence.
Process data in such a way that makes it hard to trace to the person which the data concerns.
Search for and retrieve a data identifier of some kind, e.g. a database entry accession.
Generate a checksum of a molecular sequence.
Construct a bibliography from the scientific literature.
Predict the structure of a multi-subunit protein and particularly how the subunits fit together.
Analyse the surface properties of proteins or other macromolecules, including surface accessible pockets, interior inaccessible cavities etc.
Compare two or more ontologies, e.g. identify differences.
Recognition of which format the given data is in.
'Format recognition' is not a bioinformatics-specific operation, but of great relevance in bioinformatics. Should be removed from EDAM if/when captured satisfactorily in a suitable domain-generic ontology.
The has_input "Data" (data_0006) may cause visualisation or other problems although ontologically correct. But on the other hand it may be useful to distinguish from nullary operations without inputs.
Split a file containing multiple data items into many files, each containing one item
For non-analytical operations, see the 'Processing' branch.
(jison)This is a distinction made on basis of input; all features exist can be mapped to a sequence so this isn't needed.
Predict, recognise and identify functional or other key sites within nucleic acid sequences, typically by scanning for known motifs, patterns and regular expressions.
Deposit some data in a database or some other type of repository or software system.
Group together some data entities on the basis of similarities such that entities in the same group (cluster) are more similar to each other than to those in other groups (clusters).
Construct some entity (typically a molecule sequence) from component pieces.
Convert a data set from one form to another.
Standardize or normalize data by some statistical method.
In the simplest normalisation means adjusting values measured on different scales to a common scale (often between 0.0 and 1.0), but can refer to more sophisticated adjustment whereby entire probability distributions of adjusted values are brought into alignment. Standardisation typically refers to an operation whereby a range of values are standardised to measure how many standard deviations a value is from its mean.
Combine multiple files or data items into a single file or object.
Compare two or more scientific articles.
Mathematical determination of the value of something, typically a properly of a molecule.
Generate a graph, or other visual representation, of data, showing the relationship between two or more variables.
The analysis of a image (typically a digital image) of some type in order to extract information from it.
Analysis of data from a diffraction experiment.
Analysis of cell migration images in order to study cell migration, typically in order to study the processes that play a role in the disease progression.
Processing of diffraction data into a corrected, ordered, and simplified form.
Measurement of neurites; projections (axons or dendrites) from the cell body of a neuron, from analysis of neuron images.
The evaluation of diffraction intensities and integration of diffraction maxima from a diffraction experiment.
Phase a macromolecular crystal structure, for example by using molecular replacement or experimental phasing methods.
A technique used to construct an atomic model of an unknown structure from diffraction data, based upon an atomic model of a known structure, either a related protein or the same protein from a different crystal form.
The technique solves the phase problem, i.e. retrieve information concern phases of the structure.
A method used to refine a structure by moving the whole molecule or parts of it as a rigid unit, rather than moving individual atoms.
Rigid body refinement usually follows molecular replacement in the assignment of a structure from diffraction data.
An image processing technique that combines and analyze multiple images of a particulate sample, in order to produce an image with clearer features that are more easily interpreted.
Single particle analysis is used to improve the information that can be obtained by relatively low resolution techniques, , e.g. an image of a protein or virus from transmission electron microscopy (TEM).
Compare (align and classify) multiple particle images from a micrograph in order to produce a representative image of the particle.
A micrograph can include particles in multiple different orientations and/or conformations. Particles are compared and organised into sets based on their similarity. Typically iterations of classification and alignment and are performed to optimise the final 3D EM map.
Single particle alignment and classification
Clustering of molecular sequences on the basis of their function, typically using information from an ontology of gene function, or some other measure of functional phenotype.
Classifiication (typically of molecular sequences) by assignment to some taxonomic hierarchy.
The prediction of the degree of pathogenicity of a microorganism from analysis of molecular sequences.
Analyse the correlation patterns among features/molecules across across a variety of experiments, samples etc.
Identify a correlation, i.e. a statistical relationship between two random variables or two sets of data.
Compute the covariance model for (a family of) RNA secondary structures.
RNA structure covariance model generation
Predict RNA secondary structure by analysis, e.g. probabilistic analysis, of the shape of RNA folds.
RNA secondary structure prediction (shape-based)
Prediction of nucleic-acid folding using sequence alignments as a source of data.
Nucleic acid folding prediction (alignment-based)
Count k-mers (substrings of length k) in DNA sequence data.
k-mer counting is used in genome and transcriptome assembly, metagenomic sequencing, and for error correction of sequence reads.
Reconstructing the inner node labels of a phylogenetic tree from its leafes.
Note that this is somewhat different from simply analysing an existing tree or constructing a completely new one.
Generate some data from a choosen probibalistic model, possibly to evaluate algorithms.
Generate sequences from some probabilistic model, e.g. a model that simulates evolution.
Identify or predict causes for antibiotic resistance from molecular sequence analysis.
Analysis of a set of objects, such as genes, annotated with given categories, where eventual over-/under-representation of certain categories within the studied set of objects is revealed.
Categories from a relevant ontology can be used. The input is typically a set of genes or other biological objects, possibly represented by their identifiers, and the output of the analysis is typically a ranked list of categories, each associated with a statistical metric of over-/under-representation within the studied data.
Analyse a dataset with respect to concepts from an ontology of chemical structure, leveraging chemical similarity information.
Plot an incident curve such as a survival curve, death curve, mortality curve.
Identify and map patterns of genomic variations.
Model some biological system using mathematical techniques including dynamical systems, statistical models, differential equations, and game theoretic models.
Visualise images resulting from various types of microscopy.
Annotate an image of some sort, typically with terms from a controlled vocabulary.
Replace missing data with substituted values, usually by using some statistical or other mathematical approach.
Visualise, format or render data from an ontology, typically a tree of terms.
A method for making numerical assessments about the maximum percent of time that a conformer of a flexible macromolecule can exist and still be compatible with the experimental data.
Compare the models or schemas used by two or more databases, or any other general comparison of databases rather than a detailed comparison of the entries themselves.
Simulate the bevaviour of a biological pathway or network.
Analyze read counts from RNA-seq experiments.
Identify and remove redudancy from a set of small molecule structures.
Analyze time series data from an RNA-seq experiment.
Simulate gene expression data, e.g. for purposes of benchmarking.
Simulated gene expression data generation
Identify semantic relations among entities and concepts within a text, using text mining techniques.
Re-adjust the output of mass spectrometry experiments with shifted ppm values.
Align multiple data sets using information from chromatography and/or peptide identification, from mass spectrometry experiments.
The removal of isotope peaks in a spectrum, to represent the fragment ion as one data point.
Deisotoping is commonly done to reduce complexity, and done in conjunction with the charge state deconvolution.
Technique for determining the amount of proteins in a sample.
Determination of peptide sequence from mass spectrum.
Calculate the isotope distribution of a given chemical species.
Prediction of retention time in a mass spectrometry experiment based on compositional and structural properties of the separated species.
Quantification without the use of chemical tags.
Quantification based on the use of chemical tags.
Quantification by Selected/multiple Reaction Monitoring workflow (XIC quantitation of precursor / fragment mass pair).
Calculate number of identified MS2 spectra as approximation of peptide / protein quantity.
Quantification analysis using stable isotope labeling by amino acids in cell culture.
Quantification analysis using the AB SCIEX iTRAQ isobaric labelling workflow, wherein 2-8 reporter ions are measured in MS2 spectra near 114 m/z.
Quantification analysis using labeling based on 18O-enriched H2O.
Quantification analysis using the Thermo Fisher tandem mass tag labelling workflow.
Quantification analysis using chemical labeling by stable isotope dimethylation
Peptide sequence tags are used as piece of information about a peptide obtained by tandem mass spectrometry.
Analytical process that derives a peptide's amino acid sequence from its tandem mass spectrum (MS/MS) without the assistance of a sequence database.
Identification of post-translational modifications (PTMs) of peptides/proteins in mass spectrum.
Determination of best matches between MS/MS spectrum and a database of protein or nucleic acid sequences.
Peptide database search for identification of known and unknown PTMs looking for mass difference mismatches.
Modification-tolerant peptide database search
Statistical estimation of false discovery rate from score distribution for peptide-spectrum-matches, following a peptide database search.
Statistical estimation of false discovery rate from score distribution for peptide-spectrum-matches, following a peptide database search, and by comparison to search results with a database containing incorrect information.
Analyse data in order to deduce properties of an underlying distribution or population.
A statistical calculation to estimate the relationships among variables.
Model a metabolic network. This can include 1) reconstruction to break down a metabolic pathways into reactions, enzymes, and other relevant information, and compilation of this into a mathematical model and 2) simulations of metabolism based on the model.
The terms and synyonyms here reflect that for practical intents and purposes, "pathway" and "network" can be treated the same.
Predict the effect or function of an individual single nucleotide polymorphism (SNP).
Prediction of genes or gene components from first principles, i.e. without reference to existing genes.
Prediction of genes or gene components by reference to homologous genes.
Construction of a statistical model, or a set of assumptions around some observed data, usually by describing a set of probability distributions which approximate the distribution of data.
Annotate one or more sequences with functional information, such as cellular processes or metaobolic pathways, by reference to a controlled vocabulary - invariably the Gene Ontology (GO).
Variant filtering is used to eliminate false positive variants based for example on base calling quality, strand and position information, and mapping info.
Identify binding sites in nucleic acid sequences that are statistically significantly differentially bound between sample groups.
Visualise, format or render a mass spectrum.
Filter a set of files or data items according to some property.
Identification of the best reference for mapping for a specific dataset from a list of potential references, when performing genetic variation analysis.
Label-free quantification by integration of ion current (ion counting).
Chemical tagging free amino groups of intact proteins with stable isotopes.
Labeling all proteins and (possibly) all amino acids using C-13 or N-15 enriched grown medium or feed.
This includes N-15 metabolic labeling (labeling all proteins and (possibly) all amino acids using N-15 enriched grown medium or feed) and C-13 metabolic labeling (labeling all proteins and (possibly) all amino acids using C-13 enriched grown medium or feed).
Construction of a single sequence assembly of all reads from different samples, typically as part of a comparative metagenomic analysis.
The comparison of samples from a metagenomics study, for example, by comparison of metagenome shotgun reads or assembled contig sequences, by comparison of functional profiles, or some other method.
The analysis, using proteomics techniques, to identify proteins whose encoding genes are differentially expressed under a given experimental setup.
Differential protein expression analysis
Differential protein expression profiling
The analysis, using any of diverse techniques, to identify genes that are differentially expressed under a given experimental setup.
Visualise, format or render data arising from an analysis of multiple samples from a metagenomics/community experiment.
The extrapolation of empirical characteristics of individuals or populations, backwards in time, to their common ancestors.
Ancestral reconstruction is often used to recover possible ancestral character states of ancient, extinct organisms.
Site localisation of post-translational modifications in peptide or protein mass spectra.
Operations concerning the handling and use of other tools.
An operation supporting the browsing or discovery of other tools and services.
An operation supporting the aggregation of other services (at least two) into a funtional unit, for the automation of some task.
An operation supporting the calling (invocation) of other tools and services.
A data mining method typically used for studying biological networks based on pairwise correlations between variables.
Weighted gene co-expression network analysis
Identification of protein, for example from one or more peptide identifications by tandem mass spectrometry.
Text annotation is the operation of adding notes, data and metadata, recognised entities and concepts, and their relations to a text (such as a scientific article).
A method whereby data on several variants are "collapsed" into a single covariate based on regions such as genes.
Genome-wide association studies (GWAS) analyse a genome-wide set of genetic variants in different individuals to see if any variant is associated with a trait. Traditional association techniques can lack the power to detect the significance of rare variants individually, or measure their compound effect (rare variant burden). "Collapsing methods" were developed to overcome these problems.
The analysis of microRNAs (miRNAs) : short, highly conserved small noncoding RNA molecules that are naturally occurring plant and animal genomes.
Counting and summarising the number of short sequence reads that map to genomic features.
A technique whereby molecules with desired properties and function are isolated from libraries of random molecules, through iterative cycles of selection, amplification, and mutagenesis.
The calculation of species richness for a number of individual samples, based on plots of the number of species as a function of the number of samples (rarefaction curves).
An operation which groups reads or contigs and assigns them to operational taxonomic units.
Binning methods use one or a combination of compositional features or sequence similarity.
Counting and measuring experimentally determined observations into quantities.
Quantification of data arising from RNA-Seq high-throughput sequencing, typically the quantification of transcript abundances durnig transcriptome analysis in a gene expression study.
Match experimentally measured mass spectrum to a spectrum in a spectral library or database.
Sort a set of files or data items according to some property.
Mass spectra identification of compounds that are produced by living systems. Including polyketides, terpenoids, phenylpropanoids, alkaloids and antibiotics.
Identify and assess specific genes or regulatory regions of interest that are differentially methylated.
Differentially-methylated region identification
Genotyping of multiple loci, typically characterizing microbial species isolates using internal fragments of multiple housekeeping genes.
Calculate a theoretical mass spectrometry spectra for given sequences.
3D visualization of a molecular trajectory.
Compute Essential Dynamics (ED) on a simulation trajectory: an analysis of molecule dynamics using PCA (Principal Component Analysis) applied to the atomic positional fluctuations.
Principal Component Analysis (PCA) is a multivariate statistical analysis to obtain collective variables and reduce the dimensionality of the system.
Obtain force field parameters (charge, bonds, dihedrals, etc.) from a molecule, to be used in molecular simulations
Analyse DNA sequences in order to determine an individual's DNA characteristics, for example in criminal forensics, parentage testing and so on.
Predict or detect active sites in proteins; the region of an enzyme which binds a substrate bind and catalyses a reaction.
Predict or detect ligand-binding sites in proteins; a region of a protein which reversibly binds a ligand for some biochemical purpose, such as transport or regulation of protein function.
Predict or detect metal ion-binding sites in proteins.
Model or simulate protein-protein binding using comparative modelling or other techniques.
Predict or detect RNA-binding sites in protein sequences.
Predict or detect DNA-binding sites in protein sequences.
Identify or predict intrinsically disordered regions in proteins.
Extract structured information from unstructured ("free") or semi-structured textual documents.
Retrieve resources from information systems matching a specific information need.
The determination of cytosine methylation status of specific positions in a nucleic acid sequences (usually reads from a bisulfite sequencing experiment).
The identification of changes in DNA sequence or chromosome structure, usually in the context of diagnostic tests for disease, or to study ancestry or phylogeny.
This can include indirect methods which reveal the results of genetic changes, such as RNA analysis to indicate gene expression, or biochemical analysis to identify expressed proteins.
The processing of reads from high-throughput sequencing machines.
Laboratory experiment to identify the differences between a specific genome (of an individual) and a reference genome (developed typically from many thousands of individuals). WGS re-sequencing is used as golden standard to detect variations compared to a given reference genome, including small variants (SNP and InDels) as well as larger genome re-organisations (CNVs, translocations, etc.). ows re-sequencing of complete genomes of any given organism with high resolution and high accuracy.
Amplicon sequencing is the ultra-deep sequencing of PCR products (amplicons), usually for the purpose of efficient genetic variant identification and characterisation in specific genomic regions.
Render (visualise) a network - typically a biological network of some sort.
Render (visualise) a biological pathway.
Generate, process or analyse a biological network.
Generate, process or analyse a biological pathway.
Interdisciplinary science focused on extracting information from chemical systems by data analytical approaches, for example multivariate statistics, applied mathematics, and computer science.
Assigning sequence reads to separate groups / files based on their index tag (sample origin).
NGS sequence runs are often performed with multiple samples pooled together. In such cases, an index tag (or "barcode") - a unique sequence of between 6 and 12bp - is ligated to each sample's genetic material so that the sequence reads from different samples can be identified. The process of demultiplexing (dividing sequence reads into separate files for each index tag/sample) may be performed automatically by the sequencing hardware. Alternatively the reads may be lumped together in one file with barcodes still attached, requiring you to do the splitting using software. In such cases, a "mapping" file is used which indicates which barcodes correspond to which samples.
A process used in statistics, machine learning, and information theory that reduces the number of random variables by obtaining a set of principal variables.
A dimensionality reduction process that selects a subset of relevant features (variables, predictors) for use in model construction.
A dimensionality reduction process which builds (ideally) informative and non-redundant values (features) from an initial set of measured data, to aid subsequent generalization, learning or interpretation.
Virtual screening is used in drug discovery to identify potential drug compounds. It involves searching libraries of small molecules in order to identify those molecules which are most likely to bind to a drug target (typically a protein receptor or enzyme).
Virtual screening is widely used for lead identification, lead optimization, and scaffold hopping during drug design and discovery.
Biotechnology approach that seeks to optimize cellular genetic and regulatory processes in order to increase the cells' production of a certain substance.
The application of phylogenetic and other methods to estimate paleogeographical events such as speciation.
The development and use of mathematical models and systems analysis for the description of ecological processes, and applications such as the sustainable management of resources.
Mapping between gene tree nodes and species tree nodes or branches, to analyse and account for possible differences between gene histories and species histories, explaining this in terms of gene-scale events such as duplication, loss, transfer etc.
The detection of genetic selection, or (the end result of) the process by which certain traits become more prevalent in a species than other traits.
A statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components.
Identify where sections of the genome are repeated and the number of repeats in the genome varies between individuals.
Identify deletion events causing the number of repeats in the genome to vary between individuals.
Identify duplication events causing the number of repeats in the genome to vary between individuals.
Identify copy number variations which are complex, e.g. multi-allelic variations that have many structural alleles and have rearranged multiple times in the ancestral genomes.
Identify amplification events causing the number of repeats in the genome to vary between individuals.
An adhesin is a cell-surface component that facilitate the adherence of a microorganism to a cell or surface. They are important virulence factors during establishment of infection and thus are targetted during vaccine development approaches that seek to block adhesin function and prevent adherence to host cell.
Design new protein molecules with specific structural or functional properties.
The design of small molecules with specific biological activity, such as inhibitors or modulators for proteins that are of therapeutic interest. This can involve the modification of individual atoms, the addition or removal of molecular fragments, and the use reaction-based design to explore tractable synthesis options for the small molecule.
Small molecule design can involve assessment of target druggability and flexibility, molecular docking, in silico fragment screening, molecular dynamics, and homology modeling.
There are two broad categories of small molecule design techniques when applied to the design of drugs: ligand-based drug design (e.g. ligand similarity) and structure-based drug design (ligand docking) methods. Ligand similarity methods exploit structural similarities to known active ligands, whereas ligand docking methods use the 3D structure of a target protein to predict the binding modes and affinities of ligands to it.
A category denoting a rather broad domain or field of interest, of study, application, work, data, or technology. Topics have no clearly defined borders between each other.
The processing and analysis of nucleic acid sequence, structural and other data.
Archival, processing and analysis of protein data, typically molecular sequence and structural data.
The structures of reactants or products of metabolism, for example small molecules such as including vitamins, polyols, nucleotides and amino acids.
The archival, processing and analysis of molecular sequences (monomer composition of polymers) including molecular sequence data resources, sequence sites, alignments, motifs and profiles.
The curation, processing, analysis and prediction of data about the structure of biological molecules, typically proteins and nucleic acids and other macromolecules.
This includes related concepts such as structural properties, alignments and structural motifs.
The prediction of molecular structure, including the prediction, modelling, recognition or design of protein secondary or tertiary structure or other structural features, and the folding of nucleic acid molecules and the prediction or design of nucleic acid (typically RNA) sequences with specific conformations.
This includes the recognition (prediction and assignment) of known protein structural domains or folds in protein sequence(s), for example by threading, or the alignment of molecular sequences to structures, structural (3D) profiles or templates (representing a structure or structure alignment).
The alignment (equivalence between sites) of molecular sequences, structures or profiles (representing a sequence or structure alignment).
The study of evolutionary relationships amongst organisms.
This includes diverse phylogenetic methods, including phylogenetic tree construction, typically from molecular sequence or morphological data, methods that simulate DNA sequence evolution, a phylogenetic tree or the underlying data, or which estimate or use molecular clock and stratigraphic (age) data, methods for studying gene evolution etc.
The study of gene or protein functions and their interactions in totality in a given organism, tissue, cell etc.
The conceptualisation, categorisation and nomenclature (naming) of entities or phenomena within biology or bioinformatics. This includes formal ontologies, controlled vocabularies, structured glossary, symbols and terminology or other related resource.
The search and query of data sources (typically databases or ontologies) in order to retrieve entries or other information.
The archival, curation, processing and analysis of complex biological data.
This includes data processing in general, including basic handling of files and databases, datatypes, workflows and annotation.
Rendering (drawing on a computer screen) or visualisation of molecular sequences, structures or other biomolecular data.
The study of the thermodynamic properties of a nucleic acid.
The archival, curation, processing and analysis of nucleic acid structural information, such as whole structures, structural features and alignments, and associated annotation.
Includes secondary and tertiary nucleic acid structural data, nucleic acid thermodynamic, thermal and conformational properties including DNA or DNA/RNA denaturation (melting) etc.
Topic for the study of restriction enzymes, their cleavage sites and the restriction of nucleic acids.
The mapping of complete (typically nucleotide) sequences. Mapping (in the sense of short read alignment, or more generally, just alignment) has application in RNA-Seq analysis (mapping of transcriptomics reads), variant discovery (e.g. mapping of exome capture), and re-sequencing (mapping of WGS reads).
This includes resources that aim to identify, map or analyse genetic markers in DNA sequences, for example to produce a genetic (linkage) map of a chromosome or genome or to analyse genetic linkage and synteny. It also includes resources for physical (sequence) maps of a DNA sequence showing the physical distance (base pairs) between features or landmarks such as restriction sites, cloned DNA fragments, genes and other genetic markers. It also covers for example the alignment of sequences of (typically millions) of short reads to a reference genome.
The study of codon usage in nucleotide sequence(s), genetic codes and so on.
The translation of mRNA into protein and subsequent protein processing in the cell.
Methods that aims to identify, predict, model or analyse genes or gene structure in DNA sequences.
This includes the study of promoters, coding regions, splice sites, etc. Methods for gene prediction might be ab initio, based on phylogenetic comparisons, use motifs, sequence features, support vector machine, alignment etc.
Promoters in DNA sequences (region of DNA that facilitates the transcription of a particular gene by binding RNA polymerase and transcription factor proteins).
The folding (in 3D space) of nucleic acid molecules.
Gene structure, regions which make an RNA product and features such as promoters, coding regions, gene fusion, splice sites etc.
This includes the study of promoters, coding regions etc.
This incudes operons (operators, promoters and genes) from a bacterial genome. For example the operon leader and trailer gene, gene composition of the operon and associated information.
Protein and peptide identification, especially in the study of whole proteomes of organisms.
Includes metaproteomics: proteomics analysis of an environmental sample.
Proteomics includes any methods (especially high-throughput) that separate, characterize and identify expressed proteins such as mass spectrometry, two-dimensional gel electrophoresis and protein microarrays, as well as in-silico methods that perform proteolytic or mass calculations on a protein sequence and other analyses of protein production data, for example in different cells or tissues.
The elucidation of the three dimensional structure for all (available) proteins in a given organism.
The study of the physical and biochemical properties of peptides and proteins, for example the hydrophobic, hydrophilic and charge properties of a protein.
Protein-protein, protein-DNA/RNA and protein-ligand interactions, including analysis of known interactions and prediction of putative interactions.
This includes experimental (e.g. yeast two-hybrid) and computational analysis techniques.
Protein stability, folding (in 3D space) and protein sequence-structure-function relationships. This includes for example study of inter-atomic or inter-residue interactions in protein (3D) structures, the effect of mutation, and the design of proteins with specific properties, typically by designing changes (via site-directed mutagenesis) to an existing protein.
Two-dimensional gel electrophoresis image and related data.
An analytical chemistry technique that measures the mass-to-charge ratio and abundance of ions in the gas phase.
The study of the hydrophobic, hydrophilic and charge properties of a protein.
The study of how proteins are transported within and without the cell, including signal peptides, protein subcellular localisation and export.
Enzyme or chemical cleavage sites and proteolytic or mass calculations on a protein sequence.
The comparison of two or more protein structures.
Use this concept for methods that are exclusively for protein structure.
The processing and analysis of inter-atomic or inter-residue interactions in protein (3D) structures.
Protein-protein interactions, individual interactions and networks, protein complexes, protein functional coupling etc.
Protein-ligand (small molecule) interactions.
The design of proteins with specific properties, typically by designing changes (via site-directed mutagenesis) to an existing protein.
Carbohydrates, typically including structural information.
Small molecules of biological significance, typically archival, curation, processing and analysis of structural information.
Small molecules include organic molecules, metal-organic compounds, small polypeptides, small polysaccharides and oligonucleotides. Structural data is usually included.
This concept excludes macromolecules such as proteins and nucleic acids.
This includes the structures of drugs, drug target, their interactions and binding affinities. Also the structures of reactants or products of metabolism, for example small molecules such as including vitamins, polyols, nucleotides and amino acids. Also the physicochemical, biochemical or structural properties of amino acids or peptides. Also structural and associated data for toxic chemical substances.
Edit, convert or otherwise change a molecular sequence, either randomly or specifically.
The archival, processing and analysis of the basic character composition of molecular sequences, for example character or word frequency, ambiguity, complexity, particularly regions of low complexity, and repeats or the repetitive nature of molecular sequences.
This includes repetitive elements within a nucleic acid sequence, e.g. long terminal repeats (LTRs); sequences (typically retroviral) directly repeated at both ends of a sequence and other types of repeating unit.
This includes short repetitive subsequences (repeat sequences) in a protein sequence.
Sequence composition, complexity and repeats
Conserved patterns (motifs) in molecular sequences, that (typically) describe functional or other key sites.
The comparison of two or more molecular sequences, for example sequence alignment and clustering.
The comparison might be on the basis of sequence, physico-chemical or some other properties of the sequences.
The archival, detection, prediction and analysis of positional features such as functional and other key sites, in molecular sequences and the conserved patterns (motifs, profiles etc.) that may be used to describe them.
Search and retrieve molecular sequences that are similar to a sequence-based query (typically a simple sequence).
The query is a sequence-based entity such as another sequence, a motif or profile.
The comparison and grouping together of molecular sequences on the basis of their similarities.
This includes systems that generate, process and analyse sequence clusters.
Structural features or common 3D motifs within protein structures, including the surface of a protein structure, such as biological interfaces with other molecules.
This includes conformation of conserved substructures, conserved geometry (spatial arrangement) of secondary structure or protein backbone, solvent-exposed surfaces, internal cavities, the analysis of shape, hydropathy, electrostatic patches, role and functions etc.
The processing, analysis or use of some type of structural (3D) profile or template; a computational entity (typically a numerical matrix) that is derived from and represents a structure or structure alignment.
The prediction, modelling, recognition or design of protein secondary or tertiary structure or other structural features.
The folding of nucleic acid molecules and the prediction or design of nucleic acid (typically RNA) sequences with specific conformations.
The prediction of three-dimensional structure of a (typically protein) sequence from first principles, using a physics-based or empirical scoring function and without using explicit structural templates.
The modelling of the three-dimensional structure of a protein using known sequence and structural data.
The study and simulation of molecular (typically protein) conformation using a computational model of physical forces and computer simulation.
This includes methods such as Molecular Dynamics, Coarse-grained dynamics, metadynamics, Quantum Mechanics, QM/MM, Markov State Models, etc. This includes resources concerning flexibility and motion in protein and other molecular structures.
The modelling the structure of proteins in complex with small molecules or other macromolecules.
The prediction of secondary or supersecondary structure of protein sequences.
The prediction of tertiary structure of protein sequences.
The recognition (prediction and assignment) of known protein structural domains or folds in protein sequence(s).
The alignment of molecular sequences or sequence profiles (representing sequence alignments).
This includes the generation of alignments (the identification of equivalent sites), the analysis of alignments, editing, visualisation, alignment databases, the alignment (equivalence between sites) of sequence profiles (representing sequence alignments) and so on.
The superimposition of molecular tertiary structures or structural (3D) profiles (representing a structure or structure alignment).
This includes the generation, storage, analysis, rendering etc. of structure alignments.
The alignment of molecular sequences to structures, structural (3D) profiles or templates (representing a structure or structure alignment).
Sequence profiles; typically a positional, numerical matrix representing a sequence alignment.
Sequence profiles include position-specific scoring matrix (position weight matrix), hidden Markov models etc.
The reconstruction of a phylogeny (evolutionary relatedness amongst organisms), for example, by building a phylogenetic tree.
Currently too specific for the topic sub-ontology (but might be unobsoleted).
The integrated study of evolutionary relationships and whole genome data, for example, in the analysis of species trees, horizontal gene transfer and evolutionary reconstruction.
Simulated polymerase chain reaction (PCR).
The assembly of fragments of a DNA sequence to reconstruct the original sequence.
Assembly has two broad types, de-novo and re-sequencing. Re-sequencing is a specialised case of assembly, where an assembled (typically de-novo assembled) reference genome is available and is about 95% identical to the re-sequenced genome. All other cases of assembly are 'de-novo'.
Microarrays, for example, to process microarray data or design probes and experiments.
The study of drugs and their effects or responses in living systems.
The analysis of levels and patterns of synthesis of gene products (proteins and functional RNA) including interpretation in functional terms of gene expression data.
Gene expression levels are analysed by identifying, quantifying or comparing mRNA transcripts, for example using microarrays, RNA-seq, northern blots, gene-indexed expression profiles etc.
This includes the study of codon usage in nucleotide sequence(s), genetic codes and so on.
The influence of genotype on drug response, for example by correlating gene expression or single-nucleotide polymorphisms with drug efficacy or toxicity.
The design and chemical synthesis of bioactive molecules, for example drugs or potential drug compounds, for medicinal purposes.
This includes methods that search compound collections, generate or analyse drug 3D conformations, identify drug targets with structural docking etc.
Information on a specific fish genome including molecular sequences, genes and annotation.
Information on a specific fly genome including molecular sequences, genes and annotation.
(jison)Out of EDAM scope. While very useful to have a basic set of IDs for organisms, should find a better way to provide this e.g. in bio.tools (NCBI taxon ID subset).
Information on a specific mouse or rat genome including molecular sequences, genes and annotation.
The resource may be specific to a group of mice / rats or all mice / rats.
Information on a specific worm genome including molecular sequences, genes and annotation.
The processing and analysis of the bioinformatics literature and bibliographic data, such as literature search and query.
The processing and analysis of natural language, such as scientific literature in English, in order to extract data and information, or to enable human-computer interaction.
Deposition and curation of database accessions, including annotation, typically with terms from a controlled vocabulary.
Data submission, annotation and curation
The management and manipulation of digital documents, including database records, files and reports.
An analytical technique that exploits the magenetic properties of certain atomic nuclei to provide information on the structure, dynamics, reaction state and chemical environment of molecules.
Heteronuclear Overhauser Effect Spectroscopy
Rotational Frame Nuclear Overhauser Effect Spectroscopy
The classification of molecular sequences based on some measure of their similarity.
Methods including sequence motifs, profile and other diagnostic elements which (typically) represent conserved patterns (of residues or properties) in molecular sequences.
primarily the classification of proteins (from sequence or structural data) into clusters, groups, families etc.
Sequence motifs, or sequence profiles derived from an alignment of molecular sequences of a particular type.
This includes comparison, discovery, recognition etc. of sequence motifs.
Protein chemical modifications, e.g. post-translational modifications.
Protein post-translational modifications
EDAM does not describe all possible protein modifications. For fine-grained annotation of protein modification use the Gene Ontology (children of concept GO:0006464) and/or the Protein Modifications ontology (children of concept MOD:00000)
Molecular interactions, biological pathways, networks and other models.
Molecular interactions, pathways and networks
The study and practice of information processing and use of computer information systems.
Data resources for the biological or biomedical literature, either a primary source of literature or some derivative.
Laboratory management and resources, for example, catalogues of biological resources for use in the lab including cell lines, viruses, plasmids, phages, DNA probes and primers and so on.
General cell culture or data on a specific cell lines.
The ecological and environmental sciences and especially the application of information technology (ecoinformatics).
The study of matter by studying the interference pattern from firing electrons at a sample, to analyse structures at resolutions higher than can be achieved using light.
The cell cycle including key genes and proteins.
The physicochemical, biochemical or structural properties of amino acids or peptides.
A specific organelle, or organelles in general, typically the genes and proteins (or genome and proteome).
Ribosomes, typically of ribosome-related genes and proteins.
The structures of drugs, drug target, their interactions and binding affinities.
A specific organism, or group of organisms, used to study a particular aspect of biology.
This may include information on the genome (including molecular sequences and map, genes and annotation), proteome, as well as more general information about an organism.
Whole genomes of one or more organisms, or genomes in general, such as meta-information on genomes, genome projects, gene names etc.
Particular gene(s), gene family or other gene group or system and their encoded proteins.Primarily the classification of proteins (from sequence or structural data) into clusters, groups, families etc., curation of a particular protein or protein family, or any other proteins that have been classified as members of a common group.
A protein families database might include the classifier (e.g. a sequence profile) used to build the classification.
The study of genetic constitution of a living entity, such as an individual, and organism, a cell and so on, typically with respect to a particular observable phenotypic traits, or resources concerning such traits, which might be an aspect of biochemistry, physiology, morphology, anatomy, development and so on.
Gene expression e.g. microarray data, northern blots, gene-indexed expression profiles etc.
Molecular probes (e.g. a peptide probe or DNA microarray probe) or PCR primers and hybridisation oligos in a nucleic acid sequence.
This includes the design of primers for PCR and DNA amplification or the design of molecular probes.
Diseases, including diseases in general and the genes, gene variations and proteins involved in one or more specific diseases.
A particular protein, protein family or other group of proteins.
Organism classification, identification and naming.
Archival, processing and analysis of protein sequences and sequence-based entities such as alignments, motifs and profiles.
The archival, processing and analysis of nucleotide sequences and and sequence-based entities such as alignments, motifs and profiles.
The repetitive nature of molecular sequences.
The (character) complexity of molecular sequences, particularly regions of low complexity.
A specific proteome including protein sequences and annotation.
DNA sequences and structure, including processes such as methylation and replication.
The DNA sequences might be coding or non-coding sequences.
Non-coding or functional RNA sequences, including regulatory RNA sequences, ribosomal RNA (rRNA) and transfer RNA (tRNA).
Non-coding RNA includes piwi-interacting RNA (piRNA), small nuclear RNA (snRNA) and small nucleolar RNA (snoRNA). Regulatory RNA includes microRNA (miRNA) - short single stranded RNA molecules that regulate gene expression, and small interfering RNA (siRNA).
Functional, regulatory and non-coding RNA
One or more ribosomal RNA (rRNA) sequences.
One or more transfer RNA (tRNA) sequences.
Protein secondary structure or secondary structure alignments.
This includes assignment, analysis, comparison, prediction, rendering etc. of secondary structure data.
RNA secondary or tertiary structure and alignments.
Classification of nucleic acid sequences and structures.
Primarily the classification of proteins (from sequence or structural data) into clusters, groups, families etc., curation of a particular protein or protein family, or any other proteins that have been classified as members of a common group.
Protein tertiary structural domains and folds in a protein or polypeptide chain.
This includes topological domains such as cytoplasmic regions in a protein.
This includes trans- or intra-membrane regions of a protein, typically describing physicochemical properties of the secondary structure elements. For example, the location and size of the membrane spanning segments and intervening loop regions, transmembrane region IN/OUT orientation relative to the membrane, plus the following data for each amino acid: A Z-coordinate (the distance to the membrane center), the free energy of membrane insertion (calculated in a sliding window over the sequence) and a reliability score. The z-coordinate implies information about re-entrant helices, interfacial helices, the tilt of a transmembrane helix and loop lengths.
The archival, detection, prediction and analysis ofpositional features such as functional sites in nucleotide sequences.
The detection, identification and analysis of positional features in proteins, such as functional sites.
Proteins that bind to DNA and control transcription of DNA to mRNA (transcription factors) and also transcriptional regulatory sites, elements and regions (such as promoters, enhancers, silencers and boundary elements / insulators) in nucleotide sequences.
This includes CpG rich regions (isochores) in a nucleotide sequence.
Transcription factor proteins either promote (as an activator) or block (as a repressor) the binding to DNA of RNA polymerase. Regulatory sites including transcription factor binding site as well as promoters, enhancers, silencers and boundary elements / insulators.
Transcription factors and regulatory sites
Protein phosphorylation and phosphorylation sites in protein sequences.
Biological or biomedical analytical workflows or pipelines.
Structuring data into basic types and (computational) objects.
Mitochondria, typically of mitochondrial genes and proteins.
Plants, e.g. information on a specific plant genome including molecular sequences, genes and annotation.
The resource may be specific to a plant, a group of plants or all plants.
Study of viruses, e.g. sequence and structural data, interactions of viral proteins, or a viral genome including molecular sequences, genes and annotation.
Fungi and molds, e.g. information on a specific fungal genome including molecular sequences, genes and annotation.
The resource may be specific to a fungus, a group of fungi or all fungi.
(jison)Out of EDAM scope. While very useful to have a basic set of IDs for organisms, should find a better way to provide this e.g. in bio.tools (NCBI taxon ID subset). Definition is wrong anyway.
Pathogens, e.g. information on a specific vertebrate genome including molecular sequences, genes and annotation.
The resource may be specific to a pathogen, a group of pathogens or all pathogens.
Informatics resources that aim to identify, map or analyse genetic markers in DNA sequences, for example to produce a genetic (linkage) map of a chromosome or genome or to analyse genetic linkage and synteny.
The study (typically comparison) of the sequence, structure or function of multiple genomes.
Mobile genetic elements, such as transposons, Plasmids, Bacteriophage elements and Group II introns.
Human diseases, typically describing the genes, mutations and proteins implicated in disease.
The application of information technology to immunology such as immunological processes, immunological genes, proteins and peptide ligands, antigens and so on.
Lipoproteins (protein-lipid assemblies), and proteins or region of a protein that spans or are associated with a membrane.
Proteins that catalyze chemical reaction, the kinetics of enzyme-catalysed reactions, enzyme nomenclature etc.
PCR primers and hybridisation oligos in a nucleic acid sequence.
Regions or sites in a eukaryotic and eukaryotic viral RNA sequence which directs endonuclease cleavage or polyadenylation of an RNA transcript.
CpG rich regions (isochores) in a nucleotide sequence.
Restriction enzyme recognition sites (restriction sites) in a nucleic acid sequence.
Splice sites in a nucleotide sequence or alternative RNA splicing events.
Matrix/scaffold attachment regions (MARs/SARs) in a DNA sequence.
Operons (operators, promoters and genes) from a bacterial genome.
Whole promoters or promoter elements (transcription start sites, RNA polymerase binding site, transcription factor binding sites, promoter enhancers etc) in a DNA sequence.
The molecular structure of biological molecules, particularly macromolecules such as proteins and nucleic acids.
This includes experimental methods for biomolecular structure determination, such as X-ray crystallography, nuclear magnetic resonance (NMR), circular dichroism (CD) spectroscopy, microscopy etc., including the assignment or modelling of molecular structure from such data.
Trans- or intra-membrane regions of a protein, typically describing physicochemical properties of the secondary structure elements.
The comparison of two or more molecular structures, for example structure alignment and clustering.
This might involve comparison of secondary or tertiary (3D) structural information.
The study of gene and protein function including the prediction of functional properties of a protein.
Specific bacteria or archaea, e.g. information on a specific prokaryote genome including molecular sequences, genes and annotation.
The resource may be specific to a prokaryote, a group of prokaryotes or all prokaryotes.
Experimental methods for biomolecular structure determination, such as X-ray crystallography, nuclear magnetic resonance (NMR), circular dichroism (CD) spectroscopy, microscopy etc., including the assignment or modelling of molecular structure from such data.
Cells, such as key genes and proteins involved in the cell cycle.
Topic focused on identifying, grouping, or naming things in a structured way according to some schema based on observable relationships.
Lipoproteins (protein-lipid assemblies).
Visualise a phylogeny, for example, render a phylogenetic tree.
The application of information technology to chemistry in biological research environment.
The holistic modelling and analysis of complex biological systems and the interactions therein.
This includes databases of models and methods to construct or analyse a model.
The application of statistical methods to biological problems.
Search for and retrieve molecular structures that are similar to a structure-based query (typically another structure or part of a structure).
The query is a structure-based entity such as another structure, a 3D (structural) motif, 3D profile or template.
The construction, analysis, evaluation, refinement etc. of models of a molecules properties or behaviour, including the modelling the structure of proteins in complex with small molecules or other macromolecules (docking).
The prediction of functional properties of a protein.
Single nucleotide polymorphisms (SNP) and associated data, for example, the discovery and annotation of SNPs.
Predict transmembrane domains and topology in protein sequences.
The comparison two or more nucleic acid (typically RNA) secondary or tertiary structures.
Use this concept for methods that are exclusively for nucleic acid structures.
Transcription of DNA into RNA including the regulation of transcription.
The study of cancer, for example, genes and proteins implicated in cancer.
Structural and associated data for toxic chemical substances.
A topic concerning primarily bioinformatics software tools, typically the broad function or purpose of a tool.
A general area of bioinformatics study, typically the broad scope or category of content of a bioinformatics journal or conference proceeding.
Biological nomenclature (naming), symbols and terminology.
The genes, gene variations and proteins involved in one or more specific diseases.
Protein secondary or tertiary structural data and/or associated annotation.
The study of human beings in general, including the human genome and proteome.
Informatics resource (typically a database) primarily focussed on genes.
Yeast, e.g. information on a specific yeast genome including molecular sequences, genes and annotation.
(jison) Out of EDAM scope. While very useful to have a basic set of IDs for organisms, should find a better way to provide this e.g. in bio.tools (NCBI taxon ID subset).
Eukaryotes or data concerning eukaryotes, e.g. information on a specific eukaryote genome including molecular sequences, genes and annotation.
The resource may be specific to a eukaryote, a group of eukaryotes or all eukaryotes.
Invertebrates, e.g. information on a specific invertebrate genome including molecular sequences, genes and annotation.
The resource may be specific to an invertebrate, a group of invertebrates or all invertebrates.
Vertebrates, e.g. information on a specific vertebrate genome including molecular sequences, genes and annotation.
The resource may be specific to a vertebrate, a group of vertebrates or all vertebrates.
Unicellular eukaryotes, e.g. information on a unicellular eukaryote genome including molecular sequences, genes and annotation.
The resource may be specific to a unicellular eukaryote, a group of unicellular eukaryotes or all unicellular eukaryotes.
Protein secondary or tertiary structure alignments.
The study of matter and their structure by means of the diffraction of X-rays, typically the diffraction pattern caused by the regularly spaced atoms of a crystalline sample.
Conceptualisation, categorisation and naming of entities or phenomena within biology or bioinformatics.
Ontologies, nomenclature and classification
Immunity-related proteins and their ligands.
This includes T cell receptors (TR), major histocompatibility complex (MHC), immunoglobulin superfamily (IgSF) / antibodies, major histocompatibility complex superfamily (MhcSF), etc."
Specific molecules, including large molecules built from repeating subunits (macromolecules) and small molecules of biological significance.
Toxins and the adverse effects of these chemical substances on living organisms.
Parallelised sequencing processes that are capable of sequencing many thousands of sequences simultaneously.
Informatics resources dedicated to one or more specific diseases (not diseases in general).
Variable number of tandem repeat (VNTR) polymorphism in a DNA sequence.
Microsatellite polymorphism in a DNA sequence.
Restriction fragment length polymorphisms (RFLP) in a DNA sequence.
Variable number of tandem repeat polymorphism
Includes microsatellite polymorphism in a DNA sequence. A microsatellite polymorphism is a very short subsequence that is repeated a variable number of times between individuals. These repeats consist of the nucleotides cytosine and adenosine.
Includes restriction fragment length polymorphisms (RFLP) in a DNA sequence. An RFLP is defined by the presence or absence of a specific restriction site of a bacterial restriction enzyme.
Includes single nucleotide polymorphisms (SNP) and associated data, for example, the discovery and annotation of SNPs. A SNP is a DNA sequence variation where a single nucleotide differs between members of a species or paired chromosomes in an individual.
Includes variable number of tandem repeat (VNTR) polymorphism in a DNA sequence. VNTRs occur in non-coding regions of DNA and consists sub-sequence that is repeated a multiple (and varied) number of times.
Topic for the design of nucleic acid sequences with specific conformations.
The design of primers for PCR and DNA amplification or the design of molecular probes.
Molecular secondary or tertiary (3D) structural data resources, typically of proteins and nucleic acids.
Nucleic acid (secondary or tertiary) structure, such as whole structures, structural features and associated annotation.
Molecular sequence data resources, including sequence sites, alignments, motifs and profiles.
Nucleotide sequences and associated concepts such as sequence sites, alignments, motifs and profiles.
Protein sequences and associated concepts such as sequence sites, alignments, motifs and profiles.
VT 1.5.4 Biochemistry and molecular biology
The molecular basis of biological activity, particularly the macromolecules (e.g. proteins and nucleic acids) that are essential to life.
Mammals, e.g. information on a specific mammal genome including molecular sequences, genes and annotation.
The degree of variation of life forms within a given ecosystem, biome or an entire planet.
The comparison, grouping together and classification of macromolecules on the basis of sequence similarity.
This includes the results of sequence clustering, ortholog identification, assignment to families, annotation etc.
The study of genes, genetic variation and heredity in living organisms.
The genes and genetic mechanisms such as Mendelian inheritance that underly continuous phenotypic traits (such as height or weight).
The distribution of allele frequencies in a population of organisms and its change subject to evolutionary processes including natural selection, genetic drift, mutation and gene flow.
Regulatory RNA sequences including microRNA (miRNA) and small interfering RNA (siRNA).
The documentation of resources such as tools, services and databases and how to get help.
The structural and functional organisation of genes and other genetic elements.
The application of information technology to health, disease and biomedicine.
The development of organisms between the one-cell stage (typically the zygote) and the end of the embryonic stage.
The form and function of the structures of living organisms.
The scientific literature, language processing, reference information, and documentation.
This includes the documentation of resources such as tools, services and databases, user support, how to get help etc.
The study of life and living organisms, including their morphology, biochemistry, physiology, development, evolution, and so on.
The development and use of architectures, policies, practices and procedures for management of data.
The detection of the positional features, such as functional and other key sites, in molecular sequences.
The detection of positional features such as functional sites in nucleotide sequences.
The detection, identification and analysis of positional protein sequence features, such as functional sites.
Topic for modelling biological systems in mathematical terms.
The acquisition of data, typically measurements of physical systems using any type of sampling system, or by another other means.
Specific genes and/or their encoded proteins or a family or other grouping of related genes and proteins.
Topological domains such as cytoplasmic regions in a protein.
Protein sequence variants produced e.g. from alternative splicing, alternative promoter usage, alternative initiation and ribosomal frameshifting.
Regions within a nucleic acid sequence containing a signal that alters a biological function.
Nucleic acids binding to some other molecule.
This includes ribosome binding sites (Shine-Dalgarno sequence in prokaryotes), restriction enzyme recognition sites (restriction sites) etc.
This includes sites involved with DNA replication and recombination. This includes binding sites for initiation of replication (origin of replication), regions where transfer is initiated during the conjugation or mobilisation (origin of transfer), starting sites for DNA duplication (origin of replication) and regions which are eliminated through any of kind of recombination. Also nucleosome exclusion regions, i.e. specific patterns or regions which exclude nucleosomes (the basic structural units of eukaryotic chromatin which play a significant role in regulating gene expression).
Repetitive elements within a nucleic acid sequence.
This includes long terminal repeats (LTRs); sequences (typically retroviral) directly repeated at both ends of a defined sequence and other types of repeating unit.
Coding sequences for a signal or transit peptide.
Sequence tagged sites (STS) in nucleic acid sequences.
The determination of complete (typically nucleotide) sequences, including those of genomes (full genome sequencing, de novo sequencing and resequencing), amplicons and transcriptomes.
Targeted next-generation sequencing panels
The analysis of protein-DNA interactions where chromatin immunoprecipitation (ChIP) is used in combination with massively parallel DNA sequencing to identify the binding sites of DNA-associated proteins.
A topic concerning high-throughput sequencing of cDNA to measure the RNA content (transcriptome) of a sample, for example, to investigate how different alleles of a gene are expressed, detect post-transcriptional mutations or identify gene fusions.
This includes small RNA profiling (small RNA-Seq), for example to find novel small RNAs, characterize mutations and analyze expression of small RNAs.
DNA methylation including bisulfite sequencing, methylation sites and analysis, for example of patterns and profiles of DNA methylation in a population, tissue etc.
The systematic study of metabolites, the chemical processes they are involved, and the chemical fingerprints of specific cellular processes in a whole cell, tissue, organ or organism.
The study of the epigenetic modifications of a whole cell, tissue, organism etc.
Epigenetics concerns the heritable changes in gene expression owing to mechanisms other than DNA sequence variation.
The study of genetic material recovered from environmental samples, and associated environmental data.
Variation in chromosome structure including microscopic and submicroscopic types of variation such as deletions, duplications, copy-number variants, insertions, inversions and translocations.
DNA-histone complexes (chromatin), organisation of chromatin into nucleosomes and packaging into higher-order structures.
A topic concerning high-throughput sequencing of randomly fragmented genomic DNA, for example, to investigate whole-genome sequencing and resequencing, SNP discovery, identification of copy number variations and chromosomal rearrangements.
The alignment of sequences of (typically millions) of short reads to a reference genome. This is a specialised topic within sequence alignment, especially because of complications arising from RNA splicing.
Experimental techniques that combine chromatin immunoprecipitation ('ChIP') with microarray ('chip'). ChIP-on-chip is used for high-throughput study protein-DNA interactions.
The protection of data, such as patient health data, from damage or unwanted access from unauthorised users.
Chemical substances and physico-chemical processes and that occur within living organisms.
The study of evolutionary relationships amongst organisms from analysis of genetic information (typically gene or protein sequences).
Topic concerning the study of heritable changes, for example in gene expression or phenotype, caused by mechanisms other than changes in the DNA sequence.
This includes sub-topics such as histone modification and DNA methylation (methylation sites and analysis, for example of patterns and profiles of DNA methylation in a population, tissue etc.)
The exploitation of biological process, structure and function for industrial purposes, for example the genetic manipulation of microorganisms for the antibody production.
Phenomes, or the study of the change in phenotype (the physical and biochemical traits of organisms) in response to genetic and environmental factors.
The evolutionary processes, from the genetic to environmental scale, that produced life in all its diversity.
The functions of living organisms and their constituent parts.
Research in support of healing by diagnosis, treatment, and prevention of disease.
The study of the nervous system and brain; its anatomy, physiology and function.
Topic concerning the the patterns, cause, and effect of disease within populations.
The use of physics to study biological system.
The development and application of theory, analytical methods, mathematical models and computational simulation of biological systems.
This includes the modeling and treatment of biological processes and systems in mathematical terms (theoretical biology).
The analysis of transcriptomes, or a set of all the RNA molecules in a specific cell, tissue etc.
VT 1.7.6 Inorganic and nuclear chemistry
The composition and properties of matter, reactions, and the use of reactions to create new substances.
The study of numbers (quantity) and other topics including structure, space, and change.
The theory and practical use of computer systems.
The study of matter, space and time, and related concepts such as energy and force.
RNA splicing; post-transcription RNA modification involving the removal of introns and joining of exons.
This includes the study of splice sites, splicing patterns, alternative splicing events and variants, isoforms, etc..
The structure and function of genes at a molecular level.
The branch of medicine that deals with the prevention, diagnosis and management of transmissable disease with clinically evident illness resulting from infection with pathogenic biological agents (viruses, bacteria, fungi, protozoa, parasites and prions).
Topic concerning the development and application of theory, analytical methods, mathematical models and computational simulation of chemical systems.
The branch of medicine that deals with the anatomy, functions and disorders of the nervous system.
VT 3.2.4 Cardiac and Cardiovascular systems
The diseases and abnormalities of the heart and circulatory system.
The discovery and design of drugs or potential drug compounds.
Repositories of biological samples, typically human, for basic biological and clinical research.
Laboratory study of mice, for example, phenotyping, and mutagenesis of mouse cell lines.
Collections of microbial cells including bacteria, yeasts and moulds.
Collections of cells grown under laboratory conditions, specifically, cells from multi-cellular eukaryotes and especially animal cells.
Collections of DNA, including both collections of cloned molecules, and populations of micro-organisms that store and propagate cloned DNA.
'translating' the output of basic and biomedical research into better diagnostic tools, medicines, medical procedures, policies and advice.
Collections of chemicals, typically for use in high-throughput screening experiments.
Topic concerning biological science that is (typically) performed in the context of medicine.
Topic concerning the identity of biological entities, or reports on such entities, and the mapping of entities and records in different databases.
The search and retrieval from a database on the basis of molecular sequence similarity.
Objective indicators of biological state often used to assess health, and determinate treatment.
The procedures used to conduct an experiment.
The development of policies, models and standards that cover data acquisition, storage and integration, such that it can be put to use, typically through a process of systematically applying statistical and / or logical techniques to describe, illustrate, summarise or evaluate data.
The combination and integration of data from different sources, for example into a central repository or warehouse, to provide users with a unified view of these data.
Any matter, surface or construct that interacts with a biological system.
The use of synthetic chemistry to study and manipulate biological systems.
The study of the separation, identification, and quantification of the chemical components of natural and artificial materials.
The use of chemistry to create new compounds.
The process that leads from an original formulation of a computing problem to executable programs.
The process of bringing a new drug to market once a lead compounds has been identified through drug discovery.
The process of formulating and administering a pharmaceutical compound to achieve a therapeutic effect.
The study of how a drug interacts with the body.
The discovery, development and approval of medicines.
The safety (or lack) of drugs and other medical interventions.
The detection, assesment, understanding and prevention of adverse effects of medicines.
Pharmacovigilence concerns safety once a drug has gone to market.
The testing of new medicines, vaccines or procedures on animals (preclinical) and humans (clinical) prior to their approval by regulatory authorities.
This includes diffraction experiments that are based upon the interference of waves, typically electromagnetic waves such as X-rays or visible light, by some object being studied, typical in order to produce an image of the object or determine its structure.
The use of imaging techniques to understand biology.
The use of imaging techniques for clinical purposes for medical research.
The use of optical instruments to magnify the image of an object.
The use of animals and alternatives in experimental research.
The study of organisms in the ocean or brackish waters.
The identification of molecular and genetic causes of disease and the development of interventions to correct them.
The study of the effects of food components on the metabolism, health, performance and disease resistance of humans and animals. It also includes the study of human behaviours related to food choices.
The collective characterisation and quantification of pools of biological molecules that translate into the structure, function, and dynamics of an organism or organisms.
The processes that need to be in place to ensure the quality of products for human or animal use.
The protection of public health by controlling the safety and efficacy of products in areas including pharmaceuticals, veterinary medicine, medical devices, pesticides, agrochemicals, cosmetics, and complementary medicines.
Biomedical approaches to clinical interventions that involve the use of stem cells.
An interdisciplinary field of study that looks at the dynamic systems of the human body as part of an integrted whole, incoporating biochemical, physiological, and environmental interactions that sustain life.
Topic concerning the branch of medicine that deals with the prevention, diagnosis, and treatment of disease, disorder and injury in animals.
The application of biological concepts and methods to the analytical and synthetic methodologies of engineering.
The branch of medicine dealing with the diagnosis, treatment and prevention of disease in older people, and the problems specific to aging.
Health issues related to the immune system and their prevention, diagnosis and mangement.
Allergy, clinical immunology and immunotherapeutics
The prevention of pain and the evaluation, treatment and rehabilitation of persons in pain.
VT 3.2.5 Critical care/Emergency medicine
The multidisciplinary that cares for patients with acute, life-threatening illness or injury.
VT 3.2.7 Dermatology and venereal diseases
The branch of medicine that deals with prevention, diagnosis and treatment of disorders of the skin, scalp, hair and nails.
The study, diagnosis, prevention and treatments of disorders of the oral cavity, maxillofacial area and adjacent structures.
The branch of medicine that deals with the prevention, diagnosis, and treatment of disorders of the ear, nose and throat.
The branch of medicine dealing with diseases of endocrine organs, hormone systems, their target organs, and disorders of the pathways of glucose and lipid metabolism.
The branch of medicine that deals with the blood, blood-forming organs and blood diseases.
VT 3.2.8 Gastroenterology and hepatology
The branch of medicine that deals with disorders of the oesophagus, stomach, duodenum, jejenum, ileum, large intestine, sigmoid colon and rectum.
The study of the biological and physiological differences between males and females and how they effect differences in disease presentation and management.
The branch of medicine that deals with the health of the female reproductive system, pregnancy and birth.
The branch of medicine that deals with the liver, gallbladder, bile ducts and bile.
The branch of medicine that deals with the infectious diseases of the tropics.
The branch of medicine that treats body wounds or shock produced by sudden physical injury, as from violence or accident.
The branch of medicine that deals with the diagnosis, management and prevention of poisoning and other adverse health effects caused by medications, occupational and environmental toxins, and biological agents.
The branch of medicine that deals with the prevention, diagnosis, and treatment of disorders of the muscle, bone and connective tissue. It incorporates aspects of orthopaedics, rheumatology, rehabilitation medicine and pain medicine.
The branch of medicine that deals with disorders of the eye, including eyelid, optic nerve/visual pathways and occular muscles.
The branch of medicine that deals with the medical care of infants, children and adolescents.
The branch of medicine that deals with the mangement of mental illness, emotional disturbance and abnormal behaviour.
The health of the reproductive processes, functions and systems at all stages of life.
The use of operative, manual and instrumental techniques on a patient to investigate and/or treat a pathological condition or help improve bodily function or appearance.
The branches of medicine and physiology focussing on the function and disorders of the urinary system in males and females, the reproductive system in males, and the kidney.
VT 3.2.12 Integrative and Complementary medicine
Medical therapies that fall beyond the scope of conventional medicine but may be used alongside it in the treatment of disease and ill health.
Techniques that uses magnetic fields and radiowaves to form images, typically to investigate the anatomy and physiology of the human body.
The study of matter by studying the diffraction pattern from firing neutrons at a sample, typically to determine atomic and/or magnetic structure.
Imaging in sections (sectioning), through the use of a wave-generating device (tomograph) that generates an image (a tomogram).
The discovery of patterns in large data sets and the extraction and trasnsformation of those patterns into a useful format.
VT 1.2.2 Artificial Intelligence (expert systems, machine learning, robotics)
A topic concerning the application of artificial intelligence methods to algorithms, in order to create methods that can learn from data in order to generate an ouput, rather than relying on explicitly encoded information only.
The general handling of data stored in digital archives such as databanks, databases proper, web portals and other data resources.
This includes databases for the results of scientific experiments, the application of high-throughput technology, computational analysis and the scientific literature. It covers the management and manipulation of digital documents, including database records, files and reports.
Animals, e.g. information on a specific animal genome including molecular sequences, genes and annotation.
The biology, archival, detection, prediction and analysis of positional features such as functional and other key sites, in protein sequences and the conserved patterns (motifs, profiles etc.) that may be used to describe them.
A signal peptide coding sequence encodes an N-terminal domain of a secreted protein, which is involved in attaching the polypeptide to a membrane leader sequence. A transit peptide coding sequence encodes an N-terminal domain of a nuclear-encoded organellar protein; which is involved in import of the protein into the organelle.
The biology, archival, detection, prediction and analysis of positional features such as functional and other key sites, in nucleic acid sequences and the conserved patterns (motifs, profiles etc.) that may be used to describe them.
Sequence tagged sites are short DNA sequences that are unique within a genome and serve as a mapping landmark, detectable by PCR they allow a genome to be mapped via an ordering of STSs.
Transcription of DNA into RNA and features of a messenger RNA (mRNA) molecules including precursor RNA, primary (unprocessed) transcript and fully processed molecules.
This includes Introns, and protein-coding regions including coding sequences (CDS), exons, translation initiation sites and open reading frames. Also expressed sequence tag (EST) or complementary DNA (cDNA) sequences.
This includes coding sequences for a signal or transit peptide. A signal peptide coding sequence encodes an N-terminal domain of a secreted protein, which is involved in attaching the polypeptide to a membrane leader sequence. A transit peptide coding sequence encodes an N-terminal domain of a nuclear-encoded organellar protein; which is involved in import of the protein into the organelle.
This includes regions or sites in a eukaryotic and eukaryotic viral RNA sequence which directs endonuclease cleavage or polyadenylation of an RNA transcript. A polyA signal is required for endonuclease cleavage of an RNA transcript that is followed by polyadenylation. A polyA site is a site on an RNA transcript to which adenine residues will be added during post-transcriptional polyadenylation.
Protein-ligand (small molecule) interaction(s).
Genotype experiment including case control, population, and family studies. These might use array based methods and re-sequencing methods.
Genome-wide association study experiments.
This might specify which raw data file relates to which sample and information on hybridisations, e.g. which are technical and which are biological replicates.
This includes two-dimensional gel electrophoresis (2D PAGE) experiments, gels or spots in a gel. Also mass spectrometry - an analytical chemistry technique that measures the mass-to-charge ratio and abundance of ions in the gas phase. Also Northern blot experiments.
Binding sites in proteins, including cleavage sites (for a proteolytic enzyme or agent), key residues involved in protein folding, catalytic residues (active site) of an enzyme, ligand-binding (non-catalytic) residues of a protein, such as sites that bind metal, prosthetic groups or lipids, RNA and DNA-binding proteins and binding sites etc.
Secondary structure (predicted or real) of a protein, including super-secondary structure.
The location and size of the secondary structure elements and intervening loop regions is typically given. The report can include disulphide bonds and post-translationally formed peptide bonds (crosslinks).
The application of mathematics to specific problems in science, typically by the formulation and analysis of mathematical models.
The study of abstract mathematical concepts.
The control of data entry and maintenance to ensure the data meets defined standards, qualities or constraints.
The quality, integrity, and cleaning up of data.
The study of organisms in freshwater ecosystems.
The study of inheritance in human beings.
Health problems that are prevalent in tropical and subtropical regions.
Biotechnology applied to the medical sciences and the development of medicines.
An approach to medicine whereby decisions, practices and are tailored to the individual patient based on their predicted response or risk of disease.
Experimental techniques to purify a protein-DNA crosslinked complex. Usually sequencing follows e.g. in the techniques ChIP-chip, ChIP-seq and MeDIP-seq.
Laboratory technique to sequence the complete DNA sequence of an organism's genome at a single time.
Laboratory technique to sequence the methylated regions in DNA.
Methylated DNA immunoprecipitation (MeDIP)
Laboratory technique to sequence all the protein-coding regions in a genome, i.e., the exome.
Exome sequencing is considered a cheap alternative to whole genome sequencing.
The design of an experiment intended to test a hypothesis, and describe or explain empirical data obtained under various experimental conditions.
The design of an experiment involving non-human animals.
The ecology of microorganisms including their relationship with one another and their environment.
An antibody-based technique used to map in vivo RNA-protein interactions.
Large-scale study (typically comparison) of DNA sequences of populations.
Multidisciplinary study, research and development within the field of agriculture.
Approach which samples, in parallel, all genes in all organisms present in a given sample, e.g. to provide insight into biodiversity and function.
Study of the environment, the interactions between its physical, chemical, and biological components and it's effect on life. Also how humans impact upon the environment, and how we can manage and utilise natural resources.
The study and simulation of molecular conformations using a computational model and computer simulations.
This includes methods such as Molecular Dynamics, Coarse-grained dynamics, metadynamics, Quantum Mechanics, QM/MM, Markov State Models, etc.
The application of multi-disciplinary science and technology for the construction of artificial biological systems for diverse applications.
The application of biotechnology to directly manipulate an organism's genes.
A field of biological research focused on the discovery and identification of peptides, typically by comparing mass spectra against a protein database.
A biomedical field that bridges immunology and genetics, to study the genetic basis of the immune system.
This involves the study of often complex genetic traits underlying diseases involving defects in the immune system. For example, identifying target genes for therapeutic approaches, or genetic variations involved in immunological pathology.
Cytometry is the measurement of the characteristics of cells.
Molecular biology methods used to analyze the spatial organization of chromatin in a cell.
The study of microbe gene expression within natural environments (i.e. the metatranscriptome).
Metatranscriptomics methods can be used for whole gene expression profiling of complex microbial communities.
The reconstruction and analysis of genomic information in extinct species.
The biological classification of organisms by categorizing them in groups ("clades") based on their most recent common ancestor.
The study of the process and mechanism of change of biomolecules such as DNA, RNA, and proteins across generations.
Immunoinformatics is the field of computational biology that deals with the study of immunoloogical questions. Immunoinformatics is at the interface between immunology and computer science. It takes advantage of computational, statistical, mathematical approaches and enhances the understanding of immunological knowledge.
A diagnostic imaging technique based on the application of ultrasound.
Experimental approaches to determine the rates of metabolic reactions - the metabolic fluxes - within a biological entity.
The "fluxome" is the complete set of metabolic fluxes in a cell, and is a dynamic aspect of phenotype.
An experiment for studying protein-protein interactions.
This used to have the ID http://edamontology.org/topic_3557 but the numerical part (owing to an error) duplicated http://edamontology.org/operation_3557 ('Imputation'). ID of this concept set to http://edamontology.org/topic_3957 in EDAM 1.24.
A DNA structural variation, specifically a duplication or deletion event, resulting in sections of the genome to be repeated, or the number of repeats in the genome to vary between individuals.
The branch of genetics concerned with the relationships between chromosomes and cellular behaviour, especially during mitosis and meiosis.
The design of vaccines to protect against a particular pathogen, including antigens, delivery systems, and adjuvants to elicit a predictable immune response against specific epitopes.
The study of immune system as a whole, its regulation and response to pathogens using genome-wide approaches.
The study of the phenomena whereby the effects of one locus mask the allelic effects of another, such as how dominant alleles mask the effects of the recessive alleles at the same locus.
An obsolete concept (redefined in EDAM).
Needed for conversion to the OBO format.