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Bioinformatics Advance Access originally published online on March 29, 2005
Bioinformatics 2005 21(10):2287-2293; doi:10.1093/bioinformatics/bti374
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Quasi-consensus-based comparison of profile hidden Markov models for protein sequences

Robel Y. Kahsay 1, Guoli Wang 2, Guang Gao 1, Li Liao 1,3,* and Roland Dunbrack 2,*

1Delaware Biotechnology Institute Newark, DE 19715, USA
2Fox Chase Cancer Center Philadelphia, PA 19111, USA
3Department of Computer and Information Sciences, University of Delaware Newark, DE 19716, USA

*To whom correspondence should be addressed.

A simple approach for the sensitive detection of distant relationships among protein families and for sequence–structure alignment via comparison of hidden Markov models based on their quasi-consensus sequences is presented. Using a previously published benchmark dataset, the approach is demonstrated to give better homology detection and yield alignments with improved accuracy in comparison to an existing state-of-the-art dynamic programming profile–profile comparison method. This method also runs significantly faster and is therefore suitable for a server covering the rapidly increasing structure database. A server based on this method is available at http://liao.cis.udel.edu/website/servers/modmod

Contact: roland.dunbrack{at}fccc.edu; lliao{at}mail.eecis.udel.edu


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