Gene Ontology Consortium: The Gene Ontology (GO) database and informatics resource

By M. Harris, Jennifer I. Clark, A. Ireland, Jane Lomax, Michael Ashburner, R. Foulger, Karen Eilbeck, Suzanna Lewis, B. Marshall, C. Mungall and 50 more. Nucleic Acids Res., 2004

4,608 citations recorded by the source corpus.

The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the annotation of genes, gene products and sequences. Many model organism databases and genome annotation groups use the GO and contribute their annotation sets to the GO resource. The GO database integrates the vocabularies and contributed annotations and provides full access to this information in several formats. Members of the GO Consortium continually work collectively, involving outside experts as needed, to expand and update the GO vocabularies. The GO Web resource also provides access to extensive documentation about the GO project and links to applications that use GO data for functional analyses.

Subfields: Molecular Biology

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Citations in the corpus

BioGRID: a general repository for interaction datasets (2005, background): “Spurred on by these potential applications, signiﬁcant efforts to curate interaction data from the primary literature are underway by several databases (6–11), as well as by the Gene Ontology (GO) consortium (26).”
Understanding eukaryotic linear motifs and their role in cell signaling and regulation. (2008, background): “An inspection of the Gene Ontology (GO) (1) gives a sense of the huge range of different functions that proteins are involved in.”
A review of connectivity map and computational approaches in pharmacogenomics (2017, methodology): “They used CMap and gene ontology (GO) [44] modules to partition genes into small biological categories and performed expression pattern comparison within each category [43].”
OMA 2011: orthology inference among 1000 complete genomes (2010, methodology): “With each new OMA release, we retrieve the latest annotations from the GO consortium (29) and from the GOA database (30), and map them to all relevant sequences in OMA.”
Mining Multi-label Data (2010, background): “This is the case for the Gene Ontology (GO) [57], which covers several domains of molecular and cellular biology.”
Toward a Comprehensive Atlas of the Physical Interactome of Saccharomyces cerevisiae*S (2007, positive): “Gene Ontology (GO) and GOslim Annotations—GO (13) and GOslim annotations were obtained from SGD (14) on March 7, 2006.”
Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. (2007, methodology): “For example, null sets for microarray-based con- cepts were defined as all genes measured on a microarray platform, whereas null sets for Gene Ontology–based concepts were defined as all genes with at least one Gene Ontology annotation.”
ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa Gene Expression Data with Denoising Autoencoders Illuminates Microbe-Host Interactions (2016, methodology): “A functional enrichment analysis by use of Gene Ontology (GO) (29) and KEGG (25) terms found that the HW genes in node 30 included those associated with the surface-exposed portions of type IV pili ( pilA , pilC , pilV , pilW , pilY1 , and pilY2 ) and the ﬂagellum ( ﬂgK , ﬂgL , ﬂiC , and ﬂiD ) (see…”