Онтология генов: унификация представления атрибутов генов и генопродуктов.

Bioinformatics initiative
The Gene Ontology (GO) is a major bioinformatics initiative to unify the representation of gene and gene product attributes across all species. More specifically, the project aims to: 1) maintain and develop its controlled vocabulary of gene and gene product attributes; 2) annotate genes and gene products, and assimilate and disseminate annotation data; and 3) provide tools for easy access to all aspects of the data provided by the project, and to enable functional interpretation of experimental data using the GO, for example via enrichment analysis. GO is part of a larger classification effort, the Open Biomedical Ontologies, being one of the Initial Candidate Members of the OBO Foundry. Whereas gene nomenclature focuses on gene and gene products, the Gene Ontology focuses on the function of the genes and gene products. The GO also extends the effort by using a markup language to make the data (not only of the genes and their products but also of curated attributes) machine readable, and to do so in a way that is unified across all species (whereas gene nomenclature conventions vary by biological taxon).

The Gene Ontology was originally constructed in 1998 by a consortium of researchers studying the genomes of three model organisms: Drosophila melanogaster (fruit fly), Mus musculus (mouse), and Saccharomyces cerevisiae (brewer's or baker's yeast). Many other Model Organism Databases have joined the Gene Ontology Consortium, contributing not only to annotation data, but also to the development of ontologies and tools to view and apply the data. Many major plant, animal, and microorganism databases make a contribution towards this project. As of July 2019, the GO contains 44,945 terms; there are 6,408,283 annotations to 4,467 different biological organisms.

Genome annotation encompasses the practice of capturing data about a gene product, and GO annotations use terms from the GO to do so. Annotations from GO curators are integrated and disseminated on the GO website, where they can be downloaded directly or viewed online using AmiGO. 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). In 2010, over 98% of all GO annotations were inferred computationally, not by curators, but as of July 2, 2019, only about 30% of all GO annotations were inferred computationally. As these annotations are not checked by a human, the GO Consortium considers them to be marginally less reliable and they are commonly to a higher level, less detailed terms. Full annotation data sets can be downloaded from the GO website. To support the development of annotation, the GO Consortium provides workshops and mentors new groups of curators and developers. Many machine learning algorithms have been designed and implemented to predict Gene Ontology annotations.

There are a large number of tools available, both online and for 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 is a web based application that allows users to query, browse, and visualize ontologies and gene product annotation data. It also has a BLAST tool, tools allowing analysis of larger data sets, and an interface to query the GO database directly. AmiGO can be used online at the GO website to access the data provided by the GO Consortium or downloaded and installed for local use on any database employing the GO database schema (e. g.). It is free open source software and is available as part of the go dev software distribution. OBO Edit is an open source, platform independent ontology editor developed and maintained by the Gene Ontology Consortium. It is implemented in Java and uses a graph oriented approach to display and edit ontologies. OBO Edit includes a comprehensive search and filter interface, with the option to render subsets of terms to make them visually distinct; the user interface can also be customized according to user preferences. OBO Edit also has a reasoner that can infer links that have not been explicitly stated based on existing relationships and their properties. Although it was developed for biomedical ontologies, OBO Edit can be used to view, search, and edit any ontology. It is freely available to download.

The Gene Ontology Consortium is the set of biological databases and research groups actively involved in the gene ontology project. This includes a number of model organism databases and multi species protein databases, software development groups, and a dedicated editorial office.