• Medientyp: E-Artikel
  • Titel: FuncBase : a resource for quantitative gene function annotation
  • Beteiligte: Beaver, John E.; Taşan, Murat; Gibbons, Francis D.; Tian, Weidong; Hughes, Timothy R.; Roth, Frederick P.
  • Erschienen: Oxford University Press (OUP), 2010
  • Erschienen in: Bioinformatics, 26 (2010) 14, Seite 1806-1807
  • Sprache: Englisch
  • DOI: 10.1093/bioinformatics/btq265
  • ISSN: 1367-4811; 1367-4803
  • Schlagwörter: Computational Mathematics ; Computational Theory and Mathematics ; Computer Science Applications ; Molecular Biology ; Biochemistry ; Statistics and Probability
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  • Beschreibung: <jats:title>Abstract</jats:title> <jats:p>Summary: Computational gene function prediction can serve to focus experimental resources on high-priority experimental tasks. FuncBase is a web resource for viewing quantitative machine learning-based gene function annotations. Quantitative annotations of genes, including fungal and mammalian genes, with Gene Ontology terms are accompanied by a community feedback system. Evidence underlying function annotations is shown. For example, a custom Cytoscape viewer shows functional linkage graphs relevant to the gene or function of interest. FuncBase provides links to external resources, and may be accessed directly or via links from species-specific databases.</jats:p> <jats:p>Availability: FuncBase as well as all underlying data and annotations are freely available via http://func.med.harvard.edu/</jats:p> <jats:p>Contact:  fritz_roth@hms.harvard.edu</jats:p>
  • Zugangsstatus: Freier Zugang