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CombFunc: predicting protein function using heterogeneous data sources

Only a small fraction of known proteins have been functionally characterized, making protein function prediction essential to propose annotations for uncharacterized proteins. In recent years many function prediction methods have been developed using various sources of biological data from protein s...

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Detalles Bibliográficos
Autores principales: Wass, Mark N., Barton, Geraint, Sternberg, Michael J. E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394346/
https://www.ncbi.nlm.nih.gov/pubmed/22641853
http://dx.doi.org/10.1093/nar/gks489
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author Wass, Mark N.
Barton, Geraint
Sternberg, Michael J. E.
author_facet Wass, Mark N.
Barton, Geraint
Sternberg, Michael J. E.
author_sort Wass, Mark N.
collection PubMed
description Only a small fraction of known proteins have been functionally characterized, making protein function prediction essential to propose annotations for uncharacterized proteins. In recent years many function prediction methods have been developed using various sources of biological data from protein sequence and structure to gene expression data. Here we present the CombFunc web server, which makes Gene Ontology (GO)-based protein function predictions. CombFunc incorporates ConFunc, our existing function prediction method, with other approaches for function prediction that use protein sequence, gene expression and protein–protein interaction data. In benchmarking on a set of 1686 proteins CombFunc obtains precision and recall of 0.71 and 0.64 respectively for gene ontology molecular function terms. For biological process GO terms precision of 0.74 and recall of 0.41 is obtained. CombFunc is available at http://www.sbg.bio.ic.ac.uk/combfunc.
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spelling pubmed-33943462012-07-30 CombFunc: predicting protein function using heterogeneous data sources Wass, Mark N. Barton, Geraint Sternberg, Michael J. E. Nucleic Acids Res Articles Only a small fraction of known proteins have been functionally characterized, making protein function prediction essential to propose annotations for uncharacterized proteins. In recent years many function prediction methods have been developed using various sources of biological data from protein sequence and structure to gene expression data. Here we present the CombFunc web server, which makes Gene Ontology (GO)-based protein function predictions. CombFunc incorporates ConFunc, our existing function prediction method, with other approaches for function prediction that use protein sequence, gene expression and protein–protein interaction data. In benchmarking on a set of 1686 proteins CombFunc obtains precision and recall of 0.71 and 0.64 respectively for gene ontology molecular function terms. For biological process GO terms precision of 0.74 and recall of 0.41 is obtained. CombFunc is available at http://www.sbg.bio.ic.ac.uk/combfunc. Oxford University Press 2012-07 2012-05-25 /pmc/articles/PMC3394346/ /pubmed/22641853 http://dx.doi.org/10.1093/nar/gks489 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Wass, Mark N.
Barton, Geraint
Sternberg, Michael J. E.
CombFunc: predicting protein function using heterogeneous data sources
title CombFunc: predicting protein function using heterogeneous data sources
title_full CombFunc: predicting protein function using heterogeneous data sources
title_fullStr CombFunc: predicting protein function using heterogeneous data sources
title_full_unstemmed CombFunc: predicting protein function using heterogeneous data sources
title_short CombFunc: predicting protein function using heterogeneous data sources
title_sort combfunc: predicting protein function using heterogeneous data sources
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394346/
https://www.ncbi.nlm.nih.gov/pubmed/22641853
http://dx.doi.org/10.1093/nar/gks489
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