Issue No. 04 - July-Aug. (2013 vol. 10)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TCBB.2013.102
Ken D. Nguyen , Dept. of Comput. Sci. & Inf. Technol., Clayton State Univ., Morrow, GA, USA
Yi Pan , Dept. of Comput. Sci., Georgia State Univ., Atlanta, GA, USA
A common and cost-effective mechanism to identify the functionalities, structures, or relationships between species is multiple-sequence alignment, in which DNA/RNA/protein sequences are arranged and aligned so that similarities between sequences are clustered together. Correctly identifying and aligning these sequence biological similarities help from unwinding the mystery of species evolution to drug design. We present our knowledge-based multiple sequence alignment (KB-MSA) technique that utilizes the existing knowledge databases such as SWISSPROT, GENBANK, or HOMSTRAD to provide a more realistic and reliable sequence alignment. We also provide a modified version of this algorithm (CB-MSA) that utilizes the sequence consistency information when sequence knowledge databases are not available. Our benchmark tests on BAliBASE, PREFAB, HOMSTRAD, and SABMARK references show accuracy improvements up to 10 percent on twilight data sets against many leading alignment tools such as ISPALIGN, PADT, CLUSTALW, MAFFT, PROBCONS, and T-COFFEE.
Databases, Bioinformatics, Computational biology, Knowledge based systems, Phylogeny, Amino acids
K. D. Nguyen and Yi Pan, "A Knowledge-Based Multiple-Sequence Alignment Algorithm," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. 4, pp. 884-896, 2013.