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Bioinformatics Advance Access originally published online on April 29, 2004
Bioinformatics 2004 20(16):2529-2533; doi:10.1093/bioinformatics/bth279
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Bioinformatics vol. 20 issue 16 © Oxford University Press 2004; all rights reserved.

Efficient combination of multiple word models for improved sequence comparison

Xiaoqiu Huang 1,*, Liang Ye 1, Hui-Hsien Chou 1,2, I-Hsuan Yang 3 and Kun-Mao Chao 3

1 Department of Computer Science and 2 Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011-1040, USA and 3 Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan

Received on January 5, 2004; revised on April 17, 2004; accepted on April 18, 2004
Advance Access Publication April 29, 2004

Motivation: Studies of efficient and sensitive sequence comparison methods are driven by a need to find homologous regions of weak similarity between large genomes.

Results: We describe an improved method for finding similar regions between two sets of DNA sequences. The new method generalizes existing methods by locating word matches between sequences under two or more word models and extending word matches into high-scoring segment pairs (HSPs). The method is implemented as a computer program named DDS2. Experimental results show that DDS2 can find more HSPs by using several word models than by using one word model.

Availability: The DDS2 program is freely available for academic use in binary code form at http://bioinformatics.iastate.edu/aat/align/align.html and in source code form from the corresponding author.

Contact: xqhuang{at}cs.iastate.edu

* To whom correspondence should be addressed.


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T.-J. Wu, Y.-H. Huang, and L.-A. Li
Optimal word sizes for dissimilarity measures and estimation of the degree of dissimilarity between DNA sequences
Bioinformatics, November 15, 2005; 21(22): 4125 - 4132.
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