Title |
Gene Ontology annotations at SGD: new data sources and annotation methods
|
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Published in |
Nucleic Acids Research, December 2007
|
DOI | 10.1093/nar/gkm909 |
Pubmed ID | |
Authors |
Eurie L. Hong, Rama Balakrishnan, Qing Dong, Karen R. Christie, Julie Park, Gail Binkley, Maria C. Costanzo, Selina S. Dwight, Stacia R. Engel, Dianna G. Fisk, Jodi E. Hirschman, Benjamin C. Hitz, Cynthia J. Krieger, Michael S. Livstone, Stuart R. Miyasato, Robert S. Nash, Rose Oughtred, Marek S. Skrzypek, Shuai Weng, Edith D. Wong, Kathy K. Zhu, Kara Dolinski, David Botstein, J. Michael Cherry |
Abstract |
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. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 8 | 8% |
Portugal | 2 | 2% |
Netherlands | 2 | 2% |
United Kingdom | 2 | 2% |
Chile | 1 | <1% |
India | 1 | <1% |
Iceland | 1 | <1% |
Germany | 1 | <1% |
Japan | 1 | <1% |
Other | 1 | <1% |
Unknown | 82 | 80% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 25 | 25% |
Researcher | 23 | 23% |
Professor > Associate Professor | 10 | 10% |
Other | 6 | 6% |
Student > Master | 6 | 6% |
Other | 18 | 18% |
Unknown | 14 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 44 | 43% |
Computer Science | 18 | 18% |
Biochemistry, Genetics and Molecular Biology | 15 | 15% |
Medicine and Dentistry | 4 | 4% |
Immunology and Microbiology | 1 | <1% |
Other | 4 | 4% |
Unknown | 16 | 16% |