A Knowledge-based Multiple Sequence Alignment Algorithm
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Authors
Ken Nguyen
Yi Pan
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Journal Article, Academic Journal
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Abstract
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 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% on twilight datasets against many leading alignment tools such as ISPALIGN, PADT, CLUSTALW, MAFFT, PROBCONS and T-COFFEE