A practical approach to significance assessment in alignment with gaps

Nicholas Chia, Ralf Bundschuh

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

Current numerical methods for assessing the statistical significance of local alignments with gaps are time consuming. Analytical solutions thus far have been limited to specific cases. Here, we present a new line of attack to the problem of statistical significance assessment. We combine this new approach with known properties of the dynamics of the global alignment algorithm and high performance numerical techniques and present a novel method for assessing significance of gaps within practical time scales. The results and performance of these new methods test very well against tried methods with drastically less effort.

Original languageEnglish (US)
Pages (from-to)429-441
Number of pages13
JournalJournal of Computational Biology
Volume13
Issue number2
DOIs
StatePublished - Mar 1 2006

Keywords

  • Gumbel distribution
  • Markov models and/or hidden markov models
  • Pairwise sequence alignment
  • Statistical significance
  • Statistics of motifs or strings

ASJC Scopus subject areas

  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Mathematics
  • Computational Theory and Mathematics

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