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Improving accuracy of multiple sequence alignment algorithms based on alignment of neighboring residues
Authors:Yue Lu and Sing-Hoi Sze
Affiliation:1.Department of Biochemistry and Biophysics, and 2.Department of Computer Science, Texas A&M University, College Station, TX 77843, USA
Abstract:While most of the recent improvements in multiple sequence alignment accuracy are due to better use of vertical information, which include the incorporation of consistency-based pairwise alignments and the use of profile alignments, we observe that it is possible to further improve accuracy by taking into account alignment of neighboring residues when aligning two residues, thus making better use of horizontal information. By modifying existing multiple alignment algorithms to make use of horizontal information, we show that this strategy is able to consistently improve over existing algorithms on a few sets of benchmark alignments that are commonly used to measure alignment accuracy, and the average improvements in accuracy can be as much as 1–3% on protein sequence alignment and 5–10% on DNA/RNA sequence alignment. Unlike previous algorithms, consistent average improvements can be obtained across all identity levels.
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