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FuncBase : a resource for quantitative gene function annotation

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...

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Detalles Bibliográficos
Autores principales: Beaver, John E., Taşan, Murat, Gibbons, Francis D., Tian, Weidong, Hughes, Timothy R., Roth, Frederick P.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2894510/
https://www.ncbi.nlm.nih.gov/pubmed/20495000
http://dx.doi.org/10.1093/bioinformatics/btq265
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author Beaver, John E.
Taşan, Murat
Gibbons, Francis D.
Tian, Weidong
Hughes, Timothy R.
Roth, Frederick P.
author_facet Beaver, John E.
Taşan, Murat
Gibbons, Francis D.
Tian, Weidong
Hughes, Timothy R.
Roth, Frederick P.
author_sort Beaver, John E.
collection PubMed
description 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. Availability: FuncBase as well as all underlying data and annotations are freely available via http://func.med.harvard.edu/ Contact: fritz_roth@hms.harvard.edu
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spelling pubmed-28945102010-07-01 FuncBase : a resource for quantitative gene function annotation Beaver, John E. Taşan, Murat Gibbons, Francis D. Tian, Weidong Hughes, Timothy R. Roth, Frederick P. Bioinformatics Applications Note 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. Availability: FuncBase as well as all underlying data and annotations are freely available via http://func.med.harvard.edu/ Contact: fritz_roth@hms.harvard.edu Oxford University Press 2010-07-15 2010-05-21 /pmc/articles/PMC2894510/ /pubmed/20495000 http://dx.doi.org/10.1093/bioinformatics/btq265 Text en © The Author(s) 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Beaver, John E.
Taşan, Murat
Gibbons, Francis D.
Tian, Weidong
Hughes, Timothy R.
Roth, Frederick P.
FuncBase : a resource for quantitative gene function annotation
title FuncBase : a resource for quantitative gene function annotation
title_full FuncBase : a resource for quantitative gene function annotation
title_fullStr FuncBase : a resource for quantitative gene function annotation
title_full_unstemmed FuncBase : a resource for quantitative gene function annotation
title_short FuncBase : a resource for quantitative gene function annotation
title_sort funcbase : a resource for quantitative gene function annotation
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2894510/
https://www.ncbi.nlm.nih.gov/pubmed/20495000
http://dx.doi.org/10.1093/bioinformatics/btq265
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