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Bioinformatics. 2013 Oct 15;29(20):2647-8. doi: 10.1093/bioinformatics/btt451. Epub 2013 Aug 5.

Pclust: protein network visualization highlighting experimental data.

Author information

1
Departments of Biophysics and Biochemistry and Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390-9050, USA.

Abstract

SUMMARY:

One approach to infer functions of new proteins from their homologs utilizes visualization of an all-against-all pairwise similarity network (A2ApsN) that exploits the speed of BLAST and avoids the complexity of multiple sequence alignment. However, identifying functions of the protein clusters in A2ApsN is never trivial, due to a lack of linking characterized proteins to their relevant information in current software packages. Given the database errors introduced by automatic annotation transfer, functional deduction should be made from proteins with experimental studies, i.e. 'reference proteins'. Here, we present a web server, termed Pclust, which provides a user-friendly interface to visualize the A2ApsN, placing emphasis on such 'reference proteins' and providing access to their full information in source databases, e.g. articles in PubMed. The identification of 'reference proteins' and the ease of cross-database linkage will facilitate understanding the functions of protein clusters in the network, thus promoting interpretation of proteins of interest.

AVAILABILITY:

The Pclust server is freely available at http://prodata.swmed.edu/pclust

PMID:
23918248
PMCID:
PMC3789550
DOI:
10.1093/bioinformatics/btt451
[Indexed for MEDLINE]
Free PMC Article
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