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Nucleic Acids Research Advance Access originally published online on December 19, 2006
Nucleic Acids Research 2007 35(2):678-686; doi:10.1093/nar/gkl1063
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Nucleic Acids Research, 2007, Vol. 35, No. 2 678-686
© 2006 The Author(s).
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Computational Biology

Dynamic use of multiple parameter sets in sequence alignment

Xiaoqiu Huang* and Douglas L. Brutlag1

Department of Computer Science, Iowa State University Ames, IA 50011-1040, USA 1 Department of Biochemistry, Stanford University School of Medicine Stanford, CA 94305-5307, USA

*To whom correspondence should be addressed: Tel: +1 515 294 2432; Fax: +1 515 294 0258; Email: xqhuang{at}cs.iastate.edu.

Received June 22, 2006. Revised November 17, 2006. Accepted November 20, 2006.

The level of conservation between two homologous sequences often varies among sequence regions; functionally important domains are more conserved than the remaining regions. Thus, multiple parameter sets should be used in alignment of homologous sequences with a stringent parameter set for highly conserved regions and a moderate parameter set for weakly conserved regions. We describe an alignment algorithm to allow dynamic use of multiple parameter sets with different levels of stringency in computation of an optimal alignment of two sequences. The algorithm dynamically considers various candidate alignments, partitions each candidate alignment into sections, and determines the most appropriate set of parameter values for each section of the alignment. The algorithm and its local alignment version are implemented in a computer program named GAP4. The local alignment algorithm in GAP4, that in its predecessor GAP3, and an ordinary local alignment program SIM were evaluated on 257 716 pairs of homologous sequences from 100 protein families. On 168 475 of the 257 716 pairs (a rate of 65.4%), alignments from GAP4 were more statistically significant than alignments from GAP3 and SIM.


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