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COFACTOR: improved protein function prediction by combining structure, sequence and protein–protein interaction information

The COFACTOR web server is a unified platform for structure-based multiple-level protein function predictions. By structurally threading low-resolution structural models through the BioLiP library, the COFACTOR server infers three categories of protein functions including gene ontology, enzyme commi...

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Detalles Bibliográficos
Autores principales: Zhang, Chengxin, Freddolino, Peter L., Zhang, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5793808/
https://www.ncbi.nlm.nih.gov/pubmed/28472402
http://dx.doi.org/10.1093/nar/gkx366
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author Zhang, Chengxin
Freddolino, Peter L.
Zhang, Yang
author_facet Zhang, Chengxin
Freddolino, Peter L.
Zhang, Yang
author_sort Zhang, Chengxin
collection PubMed
description The COFACTOR web server is a unified platform for structure-based multiple-level protein function predictions. By structurally threading low-resolution structural models through the BioLiP library, the COFACTOR server infers three categories of protein functions including gene ontology, enzyme commission and ligand-binding sites from various analogous and homologous function templates. Here, we report recent improvements of the COFACTOR server in the development of new pipelines to infer functional insights from sequence profile alignments and protein–protein interaction networks. Large-scale benchmark tests show that the new hybrid COFACTOR approach significantly improves the function annotation accuracy of the former structure-based pipeline and other state-of-the-art functional annotation methods, particularly for targets that have no close homology templates. The updated COFACTOR server and the template libraries are available at http://zhanglab.ccmb.med.umich.edu/COFACTOR/.
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spelling pubmed-57938082018-02-06 COFACTOR: improved protein function prediction by combining structure, sequence and protein–protein interaction information Zhang, Chengxin Freddolino, Peter L. Zhang, Yang Nucleic Acids Res Web Server Issue The COFACTOR web server is a unified platform for structure-based multiple-level protein function predictions. By structurally threading low-resolution structural models through the BioLiP library, the COFACTOR server infers three categories of protein functions including gene ontology, enzyme commission and ligand-binding sites from various analogous and homologous function templates. Here, we report recent improvements of the COFACTOR server in the development of new pipelines to infer functional insights from sequence profile alignments and protein–protein interaction networks. Large-scale benchmark tests show that the new hybrid COFACTOR approach significantly improves the function annotation accuracy of the former structure-based pipeline and other state-of-the-art functional annotation methods, particularly for targets that have no close homology templates. The updated COFACTOR server and the template libraries are available at http://zhanglab.ccmb.med.umich.edu/COFACTOR/. Oxford University Press 2017-07-03 2017-05-02 /pmc/articles/PMC5793808/ /pubmed/28472402 http://dx.doi.org/10.1093/nar/gkx366 Text en © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Web Server Issue
Zhang, Chengxin
Freddolino, Peter L.
Zhang, Yang
COFACTOR: improved protein function prediction by combining structure, sequence and protein–protein interaction information
title COFACTOR: improved protein function prediction by combining structure, sequence and protein–protein interaction information
title_full COFACTOR: improved protein function prediction by combining structure, sequence and protein–protein interaction information
title_fullStr COFACTOR: improved protein function prediction by combining structure, sequence and protein–protein interaction information
title_full_unstemmed COFACTOR: improved protein function prediction by combining structure, sequence and protein–protein interaction information
title_short COFACTOR: improved protein function prediction by combining structure, sequence and protein–protein interaction information
title_sort cofactor: improved protein function prediction by combining structure, sequence and protein–protein interaction information
topic Web Server Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5793808/
https://www.ncbi.nlm.nih.gov/pubmed/28472402
http://dx.doi.org/10.1093/nar/gkx366
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