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Nucleic Acids Research Advance Access originally published online on November 3, 2007
Nucleic Acids Research 2008 36(Database issue):D577-D581; doi:10.1093/nar/gkm909
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Nucleic Acids Research, 2008, Vol. 36, Database issue D577-D581
© 2007 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

This article appears in the following Nucleic Acids Research issue: Database issue [View the issue table of contents]

Articles

Gene Ontology annotations at SGD: new data sources and annotation methods

Eurie L. Hong1, Rama Balakrishnan1, Qing Dong1, Karen R. Christie1, Julie Park1, Gail Binkley1, Maria C. Costanzo1, Selina S. Dwight1, Stacia R. Engel1, Dianna G. Fisk1, Jodi E. Hirschman1, Benjamin C. Hitz1, Cynthia J. Krieger1, Michael S. Livstone2, Stuart R. Miyasato1, Robert S. Nash1, Rose Oughtred2, Marek S. Skrzypek1, Shuai Weng1, Edith D. Wong1, Kathy K. Zhu1, Kara Dolinski2, David Botstein2 and J. Michael Cherry1,*

1Department of Genetics, Stanford University, Stanford, CA, USA and 2Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA

*To whom correspondence should be addressed. Tel: 650 723 7541; Fax: 650 725 1534; Email: cherry{at}stanford.edu

Received September 17, 2007. Accepted October 6, 2007.

The Saccharomyces Genome Database (SGD; http://www.yeastgenome.org/) collects and organizes biological information about the chromosomal features and gene products of the budding yeast Saccharomyces cerevisiae. Although published data from traditional experimental methods are the primary sources of evidence supporting Gene Ontology (GO) annotations for a gene product, high-throughput experiments and computational predictions can also provide valuable insights in the absence of an extensive body of literature. Therefore, GO annotations available at SGD now include high-throughput data as well as computational predictions provided by the GO Annotation Project (GOA UniProt; http://www.ebi.ac.uk/GOA/). Because the annotation method used to assign GO annotations varies by data source, GO resources at SGD have been modified to distinguish data sources and annotation methods. In addition to providing information for genes that have not been experimentally characterized, GO annotations from independent sources can be compared to those made by SGD to help keep the literature-based GO annotations current.


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