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Bioinformatics Advance Access originally published online on May 14, 2004
Bioinformatics 2004 20(16):2676-2684; doi:10.1093/bioinformatics/bth308
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Bioinformatics vol. 20 issue 16 © Oxford University Press 2004; all rights reserved.

An efficient algorithm for optimizing whole genome alignment with noise

Prudence W. H. Wong *, T. W. Lam , N. Lu , H. F. Ting and S. M. Yiu

Department of Computer Science, University of Hong Kong, Hong Kong

Received on October 20, 2003; revised on April 13, 2004; accepted on April 28, 2004
Advance Access Publication May 14, 2004

Motivation: This paper is concerned with algorithms for aligning two whole genomes so as to identify regions that possibly contain conserved genes. Motivated by existing heuristic-based software tools, we initiate the study of an optimization problem that attempts to uncover conserved genes with a global concern. Another interesting feature in our formulation is the tolerance of noise, which also complicates the optimization problem. A brute-force approach takes time exponential in the noise level.

Results: We show how an insight into the optimization structure can lead to a drastic improvement in the time and space requirement [precisely, to O(k2n2) and O(k2n), respectively, where n is the size of the input and k is the noise level]. The reduced space requirement allows us to implement the new algorithm, called MaxMinCluster, on a PC. It is exciting to see that when tested with different real data sets, MaxMinCluster consistently uncovers a high percentage of conserved genes that have been published by GenBank. Its performance is indeed favorably compared to MUMmer (perhaps the most popular software tool for uncovering conserved genes in a whole-genome scale).

Availability: The source code is available from the website http://www.csis.hku.hk/~colly/maxmincluster/. Detailed proof of the propositions can also be found there.

Contact: whwong{at}cs.hku.hk

* To whom correspondence should be addressed.


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[Abstract] [Full Text] [PDF]


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