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. 2010;4(1):60-71.
doi: 10.1504/ijdmb.2010.030967.

Alignment of multiple proteins with an ensemble of hidden Markov models

Jia Song  1 , Chunmei Liu, Yinglei Song, Junfeng Qu, Gurdeep S Hura
Affiliations

Alignment of multiple proteins with an ensemble of hidden Markov models

Jia Song et al. Int J Data Min Bioinform. 2010.

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.

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Figures

Figure 1
Figure 1
An illustration of the alignment method: (a) firstly, given a set of sequences, the order to include the sequences in the alignment is determined; (b) secondly, an ensemble with k profile HMMs is constructed and progressively updated while the remaining unaligned sequences are aligned to the profile HMMs in the ensemble and (c) thirdly, k alignments with leading scores can be generated from the profile HMMs in the ensemble when no sequences in the set are unaligned
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