A performance enhanced PSI-BLAST based on hybrid alignment

作者：Li Yuheng; Chia Nicholas; Lauria Mario; Bundschuh Ralf^*

来源：Bioinformatics, 2011, 27(1): 31-37.

DOI：10.1093/bioinformatics/btq621

Motivation: Sequence alignment is one of the most popular tools of modern biology. NCBI's PSI-BLAST utilizes iterative model building in order to better detect distant homologs with greater sensitivity than non-iterative BLAST. However, PSI-BLAST's performance is limited by the fact that it relies on deterministic alignments. Using a semiprobabilistic alignment scheme such as Hybrid alignment should allow for better informed model building and improved identification of homologous sequences, particularly remote homologs.
Results: We have built a new version of the tool in which the Smith-Waterman alignment algorithm core is replaced by the hybrid alignment algorithm. The favorable statistical properties of the hybrid algorithm allow the introduction of position-specific gap penalties in Hybrid PSI-BLAST. This improves the position-specific modeling of protein families and results in an overall improvement of performance.

• 出版日期2011-1