ArticleNucleic acids research2017
COFACTOR: improved protein function prediction by combining structure, sequence and protein-protein interaction information.
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 293 papers.
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Who cites it
293 citing papers in PubMed, 628 citations in OpenAlex.
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233 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.