A performance enhanced PSI-BLAST based on hybrid alignment

Yuheng Li, Nicholas Chia, Mario Lauria, Ralf Bundschuh

Research output: Contribution to journalArticle

11 Scopus citations

Abstract

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 semi-probabilistic 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.

Original languageEnglish (US)
Article numberbtq621
Pages (from-to)31-37
Number of pages7
JournalBioinformatics
Volume27
Issue number1
DOIs
StatePublished - Jan 2011

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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