Gene Ontology Annotations and Resources

By Judith A. Blake, M. Dolan, H. Drabkin, David P. Hill, Ni Li, D. Sitnikov, Susan M. Bridges, S. Burgess, T. Buza, F. McCarthy and 126 more. Nucleic Acids Res., 2012

556 citations recorded by the source corpus.

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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/a5a4324eee9bade678ee95f1fff6fb0b271f9bbc

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Citations in the corpus

MycoCosm portal: gearing up for 1000 fungal genomes (2013, methodology): “Interpro, KEGG and Swiss-Prot hits are used to map gene ontology (GO) terms (21).”
BacMet: antibacterial biocide and metal resistance genes database (2013, methodology): “This was followed by searching the NCBI nonredundant protein database, UniprotKB and the Gene Ontology (33) database to identify the corresponding annotated biocideand metal-resistance genes within these databanks, including references.”
The BioGRID interaction database: 2015 update (2014, methodology): “Manual expert compilation of a comprehensive UPS gene reference list was augmented by semi-automated parsing of protein domain and protein function annotations available through a number of sequence-based databases (48,49,61–63).”
The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases (2013, background): “…all interaction evidences in the database and exports a high conﬁdence subset, with a high degree of probability that the molecule pairs described physically interact with each other, back to UniProtKB (1), neXtProt (18) and the Gene Ontology annotation project (19) in a distinct format for each.”
HAMAP in 2015: updates to the protein family classification and annotation system (2014, methodology): “Annotations are provided in the form of the human-readable UniProtKB text format and using UniProt controlled vocabularies and terms from the Gene Ontology (GO) (5).”
3did: a catalog of domain-based interactions of known three-dimensional structure (2013, methodology): “This page allows to search for a domain (either the name of the domain or its Pfam accession number can be used), a motif name, a structure (by PDB ID) or any term from the Gene Ontology (34).”