Pairwise statistical significance and empirical determination of effective gap opening penalties for protein local sequence alignment

Ankit Agrawal*, Volker P. Brendel, Xiaoqiu Huang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

We evaluate various methods to estimate pairwise statistical significance of a pairwise local sequence alignment in terms of statistical significance accuracy and compare it with popular database search programs in terms of retrieval accuracy on a benchmark database. Results indicate that using pairwise statistical significance using standard substitution matrices is significantly better than database statistical significance reported by BLAST and PSI-BLAST, and that it is comparable and at times significantly better than SSEARCH. An application of pairwise statistical significance to empirically determine effective gap opening penalties for protein local sequence alignment using the widely used BLOSUM matrices is also presented.

Original languageEnglish (US)
Pages (from-to)347-367
Number of pages21
JournalInternational Journal of Computational Biology and Drug Design
Volume1
Issue number4
DOIs
StatePublished - Jan 1 2008

Keywords

  • database statistical significance
  • gap opening penalty
  • homologs
  • pairwise local alignment
  • pairwise statistical significance
  • sequence alignment

ASJC Scopus subject areas

  • Drug Discovery
  • Computer Science Applications

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