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Nucleic Acids Research, 2004, Vol. 32, Database issue D262-D266
© 2004 Oxford University Press

The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology

Evelyn Camon*, Michele Magrane, Daniel Barrell, Vivian Lee, Emily Dimmer, John Maslen, David Binns, Nicola Harte, Rodrigo Lopez and Rolf Apweiler

European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK

*To whom correspondence should be addressed. Tel: +44 1223 494465; Fax: +44 1223 494468; Email: goa{at}ebi.ac.uk

The Gene Ontology Annotation (GOA) database (http://www.ebi.ac.uk/GOA) aims to provide high-quality electronic and manual annotations to the UniProt Knowledgebase (Swiss-Prot, TrEMBL and PIR-PSD) using the standardized vocabulary of the Gene Ontology (GO). As a supplementary archive of GO annotation, GOA promotes a high level of integration of the knowledge represented in UniProt with other databases. This is achieved by converting UniProt annotation into a recognized computational format. GOA provides annotated entries for nearly 60 000 species (GOA-SPTr) and is the largest and most comprehensive open-source contributor of annotations to the GO Consortium annotation effort. By integrating GO annotations from other model organism groups, GOA consolidates specialized knowledge and expertise to ensure the data remain a key reference for up-to-date biological information. Furthermore, the GOA database fully endorses the Human Proteomics Initiative by prioritizing the annotation of proteins likely to benefit human health and disease. In addition to a non-redundant set of annotations to the human proteome (GOA-Human) and monthly releases of its GO annotation for all species (GOA-SPTr), a series of GO mapping files and specific cross-references in other databases are also regularly distributed. GOA can be queried through a simple user-friendly web interface or downloaded in a parsable format via the EBI and GO FTP websites. The GOA data set can be used to enhance the annotation of particular model organism or gene expression data sets, although increasingly it has been used to evaluate GO predictions generated from text mining or protein interaction experiments. In 2004, the GOA team will build on its success and will continue to supplement the functional annotation of UniProt and work towards enhancing the ability of scientists to access all available biological information. Researchers wishing to query or contribute to the GOA project are encouraged to email: goa{at}ebi.ac.uk.


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 Mol. Cell. ProteomicsHome page
S. Orchard, H. Hermjakob, and R. Apweiler
Annotating the Human Proteome
Mol. Cell. Proteomics, April 1, 2005; 4(4): 435 - 440.
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 BioinformaticsHome page
A. Via, A. Zanzoni, and M. Helmer-Citterich
Seq2Struct: a resource for establishing sequence-structure links
Bioinformatics, February 15, 2005; 21(4): 551 - 553.
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 Nucleic Acids ResHome page
C. Brooksbank, G. Cameron, and J. Thornton
The European Bioinformatics Institute's data resources: towards systems biology
Nucleic Acids Res., January 1, 2005; 33(suppl_1): D46 - D53.
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 Nucleic Acids ResHome page
A. Bairoch, R. Apweiler, C. H. Wu, W. C. Barker, B. Boeckmann, S. Ferro, E. Gasteiger, H. Huang, R. Lopez, M. Magrane, et al.
The Universal Protein Resource (UniProt)
Nucleic Acids Res., January 1, 2005; 33(suppl_1): D154 - D159.
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 Nucleic Acids ResHome page
Y. Chen, Y. Zhang, Y. Yin, G. Gao, S. Li, Y. Jiang, X. Gu, and J. Luo
SPD--a web-based secreted protein database
Nucleic Acids Res., January 1, 2005; 33(suppl_1): D169 - D173.
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 Nucleic Acids ResHome page
N. Kaplan, O. Sasson, U. Inbar, M. Friedlich, M. Fromer, H. Fleischer, E. Portugaly, N. Linial, and M. Linial
ProtoNet 4.0: A hierarchical classification of one million protein sequences
Nucleic Acids Res., January 1, 2005; 33(suppl_1): D216 - D218.
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