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Bioinformatics Advance Access originally published online on March 3, 2005
Bioinformatics 2005 21(10):2271-2278; doi:10.1093/bioinformatics/bti371
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

The mutated subsequence problem and locating conserved genes

H. L. Chan 1,*, T. W. Lam 1, W. K. Sung 2, Prudence W. H. Wong 3, S. M. Yiu 1 and X. Fan 1

1Department of Computer Science, University of Hong Kong Hong Kong, China
2Department of Computer Science, National University of Singapore Singapore
3Department of Computer Science, University of Liverpool UK

*To whom correspondence should be addressed.

Motivation: For the purpose of locating conserved genes in a whole genome scale, this paper proposes a new structural optimization problem called the Mutated Subsequence Problem, which gives consideration to possible mutations between two species (in the form of reversals and transpositions) when comparing the genomes.

Results: A practical algorithm called mutated subsequence algorithm (MSS) is devised to solve this optimization problem, and it has been evaluated using different pairs of human and mouse chromosomes, and different pairs of virus genomes of Baculoviridae. MSS is found to be effective and efficient; in particular, MSS can reveal >90% of the conserved genes of human and mouse that have been reported in the literature. When compared with existing softwares MUMmer and MaxMinCluster, MSS uncovers 14 and 7% more genes on average, respectively. Furthermore, this paper shows a hybrid approach to integrate MUMmer or MaxMinCluster with MSS, which has better performance and reliability.

Availability: http://www.cs.hku.hk/~mss/

Contact: hlchan{at}cs.hku.hk


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