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Gene Ontology Annotation (GOA) | Proteomes | EBI ebi.ac.uk | GOLEM: An Interactive Graph-Based Gene-Ontology Navigation and Analysis obgyn.net | the Gene Ontology geneontology.org |
The Gene Ontology, or GO, is a major bioinformatics initiative to unify the representation of gene and gene product attributes across all species[1]. The aims of the Gene Ontology project are threefold; firstly, to maintain and further develop its controlled vocabulary of gene and gene product attributes; secondly, to annotate genes and gene products, and assimilate and disseminate annotation data; and thirdly, to provide tools to facilitate access to all aspects of the data provided by the Gene Ontology project. The GO is part of a larger classification effort, the Open Biomedical Ontologies (OBO).
[edit] GO terms and the GO ontologyThe Gene Ontology project provides an ontology of defined terms representing gene product properties. The ontology covers three domains; cellular component, the parts of a cell or its extracellular environment; molecular function, the elemental activities of a gene product at the molecular level, such as binding or catalysis; and biological process, operations or sets of molecular events with a defined beginning and end, pertinent to the functioning of integrated living units: cells, tissues, organs, and organisms. Each GO term within the ontology has a term name, which may be a word or string of words; a unique alphanumeric identifier; a definition with cited sources; and a namespace indicating the domain to which it belongs. Terms may also have synonyms, which are classed as being exactly equivalent to the term name, broader, narrower, or related; references to equivalent concepts in other databases; and comments on term meaning or usage. The GO ontology is structured as a directed acyclic graph, and each term has defined relationships to one or more other terms in the same domain, and sometimes to other domains. The GO vocabulary is designed to be species-neutral, and includes terms applicable to prokaryotes and eukaryotes, single and multicellular organisms. The GO ontology is not static, and additions, corrections and alterations are suggested by, and solicited from, members of the research and annotation communities, as well as by those directly involved in the GO project. For example, an annotator may request a specific term to represent a metabolic pathway, or a section of the ontology may be revised with the help of community experts (e.g. [2]). Suggested edits are reviewed by the ontology editors, and implemented where appropriate.
[edit] Example GO Termid: GO:0000016 name: lactase activity namespace: molecular_function def: "Catalysis of the reaction: lactose + H2O = D-glucose + D-galactose." [EC:3.2.1.108] synonym: "lactase-phlorizin hydrolase activity" BROAD [EC:3.2.1.108] synonym: "lactose galactohydrolase activity" EXACT [EC:3.2.1.108] xref: EC:3.2.1.108 xref: MetaCyc:LACTASE-RXN xref: Reactome:20536 is_a: GO:0004553 ! hydrolase activity, hydrolyzing O-glycosyl compounds Data source: [3] [edit] GO annotationGenome annotation is the practice of capturing data about a gene product, and GO annotations use terms from the GO ontology to do so. The members of the GO Consortium submit their annotation for integration and dissemination on the GO website, where they can be downloaded directly or viewed online using AmiGO. In addition to the gene product identifier and the relevant GO term, GO annotations have the following data:
The evidence code comes from the Evidence Code Ontology, a controlled vocabulary of codes covering both manual and automated annotation methods. For example, Traceable Author Statement (TAS) means a curator has read a published scientific paper and the metadata for that annotation bears a citation to that paper; Inferred from Sequence Similarity (ISS) means a human curator has reviewed the output from a sequence similarity search and verified that it is biologically meaningful. Annotations from automated processes (for example, remapping annotations created using another annotation vocabulary) are given the code Inferred from Electronic Annotation (IEA). As these annotations are not checked by a human, the GO Consortium considers them to be less reliable and does not include them in the data available online in AmiGO. Full annotation data sets can be downloaded from the GO website. [edit] Example GO AnnotationGene product: Actin, alpha cardiac muscle 1, UniProtKB:P68032 GO term: heart contraction ; GO:0060047 (biological process) Evidence code: Inferred from Mutant Phenotype (IMP) Reference: PMID:17611253 Assigned by: UniProtKB, June 06, 2008 Data source: [4] [edit] GO ToolsThere are a large number of tools available both online and to download that use the data provided by the GO project. The vast majority of these come from third parties; the GO Consortium develops and supports two tools, AmiGO and OBO-Edit. AmiGO[5] is a web-based application that allows users to query, browse and visualize ontologies and gene product annotation data. In addition, it also has a BLAST tool[6], tools allowing analysis of larger data sets[7][8], and an interface to query the GO database directly[9]. AmiGO can be used online at the GO website to access the data provided by the GO Consortium, or can be downloaded and installed for local use on any database employing the GO database schema (e.g. [10]). It is free open source software and is available as part of the go-dev software distribution[11].
[edit] The GO ConsortiumThe GO Consortium is the set of biological databases and research groups actively involved in the GO project[13]. This includes a number of model organism databases and multi-species protein databases, software development groups, and a dedicated editorial office. [edit] HistoryThe Gene Ontology was originally constructed in 1998 by a consortium of researchers studying the genome of three model organisms: Drosophila melanogaster (fruit fly), Mus musculus (mouse), and Saccharomyces cerevisiae (brewers' or bakers' yeast)[14]. Many other model organism databases have joined the Gene Ontology consortium, contributing not only annotation data, but also contributing to the development of the ontologies and tools to view and apply the data. As of January 2008, GO contains over 24,500 terms applicable to a wide variety of biological organisms. There is a significant body of literature on the development and use of GO, and it has become a standard tool in the bioinformatics arsenal. [edit] See also
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[edit] External links
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