Title: Multiple genome sequences alignment algorithm based on coding regions

Authors: Che-Lun Hung, Chun-Yuan Lin, Shih-Cheng Chang, Yeh-Ching Chung, Shu Ju Hsieh, Chuan Yi Tang, Yaw-Ling Lin

Addresses: Department of Computer Science and Communication Engineering, Providence University, 200 Chung Chi Rd., Taichung 43301, Taiwan. ' Department of Computer Science and Information Engineering, Chang Gung University, 259 Wen-Hwa 1st Road, Kwei-Shan Tao-Yuan 333, Taiwan. ' Research Center for Emerging Viral Infections, Chang Gung University, 259 Wen-Hwa 1st Road, Kwei-Shan Tao-Yuan 333, Taiwan. ' Department of Computer Science, National Tsing Hua University, 101, Section 2, Kuang-Fu Road, Hsinchu 30013, Taiwan. ' Department of Computer Science, National HsinChu Commercial and Vocational High School, 128, Xuefu Rd., East Dist., Hsinchu City 300, Taiwan. ' Department of Computer Science and Information Engineering, Providence University, 200 Chung Chi Rd., Taichung 43301, Taiwan. ' Department of Computer Science and Information Engineering, Providence University, 200 Chung Chi Rd., Taichung 43301, Taiwan

Abstract: Multiple Sequence Alignment (MSA) is the computational biology tool for facilitating the study of DNA homology, phylogeny determinations and conserved motifs. Many MSA methods have been presented to align protein, DNA, and RNA sequences successfully but not for coding region sequences. Therefore, we propose a heuristic alignment method, CORAL-M, for multiple genome sequences, especially for coding regions. CORAL-M adopts a codon-based probabilistic filtration model and the local optimal alignment solution to align multiple genome sequences in linear time. The experimental results presents that CORAL-M can find more potential function sites than that of other commonly used tools by aligning Enterovirus strains.

Keywords: MSA; multiple sequence alignment; coding regions; genome alignment; near-optimal alignment; local alignment; computational biology; region sequences; protein sequences; DNA sequences; RNA sequences; codon based models; probabilistic filtration models.

DOI: 10.1504/IJCBDD.2011.041009

International Journal of Computational Biology and Drug Design, 2011 Vol.4 No.2, pp.165 - 178

Published online: 24 Jan 2015 *

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