SNN-SB: Combining Partial Alignment Using Modified SNN Algorithm with Segment-Based for Multiple Sequence Alignments

Abstract

Abstract Multiple sequence alignment (MSA) is an essential tool in the area of bioinformatics. Many MSA algorithms have been proposed last decade, however there is still opportunity for improvement in accuracy. Including partial alignment into MSA has been proved to be an effective approach to improve the quality of results of final Multiple sequence alignment. This paper presents a novel algorithm known as SNN-SB, which used to detect the related residue of protein sequences to build partial alignments using modified Shared Near Neighbors algorithm and segment-based alignments. The partial alignment is used as guide for DIALIGN-TX algorithm to build the final MSA. In order to evaluate the effectiveness of the SNN-SB, we compared the final result with 10 outstanding MSA tools. The results of SNN-SB got the maximum mean Q score and mean SP score on IRMBASE 2.0 benchmark. Moreover, it got around 8% improvement in BAliBASE 3.0 benchmark regarding to Q score compared to DIALIGN-TX.