Alignment of multiple proteins with an ensemble of Hidden Markov Models

Authors:
Jia Song;Chunmei Liu;Yinglei Song;Junfeng Qu;Gurdeep S. Hura
Affiliations:
College of Electrical Engineering, Zhejiang University, China.;Department of Systems and Computer Science, Howard University, Washington, DC 20059, USA.;Department of Mathematics and Computer Science, University of MD Eastern Shore, Princess Anne, MD, USA.;Department of Information Technology, Clayton State University, Morrow, GA, USA.;Department of Mathematics and Computer Science, University of MD Eastern Shore, Princess Anne, MD, USA
Venue:
International Journal of Data Mining and Bioinformatics
Year:
2010

Citing 3
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Abstract

In this paper, we developed a new method that progressively constructs and updates a set of alignments by adding sequences in a certain order to each of the existing alignments. Each of the existing alignments is modelled with a profile Hidden Markov Model (HMM) and an added sequence is aligned to each of these profile HMMs. We introduced an integer parameter for the number of profile HMMs. The profile HMMs are then updated based on the alignments with leading scores. Our experiments on BaliBASE showed that our approach could efficiently explore the alignment space and significantly improve the alignment accuracy.