A community-based bioinformatics resource consisting of three structured controlled vocabularies (ontologies) for the annotation of gene products with respect to their molecular function, cellular component, and biological role in a species-independent manner. This initiative to standardize the representation of gene and gene product attributes across species and databases is an effort to address the need for consistent descriptions of gene products in different databases. The Gene Ontology project encourages input from the community into both the content of the GO and annotation using GO. There are three separate aspects to this effort: first, they write and maintain the ontologies themselves; second, they make cross-links between the ontologies and the genes and gene products in the collaborating databases; and third, they develop tools that facilitate the creation, maintenance and use of ontologies. The controlled vocabularies are structured so that you can query them at different levels: for example, you can use GO to find all the gene products in the mouse genome that are involved in signal transduction, or you can zoom in on all the receptor tyrosine kinases. This structure also allows annotators to assign properties to gene products at different levels, depending on how much is known about a gene product.
Resource Type: Resource
Version: Latest Version
The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources.
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