A practical approach to significance assessment in alignment with gaps

Nicholas Chia, Ralf Bundschuh

Research output: Contribution to journalConference article

2 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)474-488
Number of pages15
JournalLecture Notes in Bioinformatics (Subseries of Lecture Notes in Computer Science)
Volume3500
DOIs
StatePublished - 2005
Event9th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2005 - Cambridge, MA, United States
Duration: May 14 2005May 18 2005

Keywords

  • Asymmetric exclusion process
  • Extreme value distribution
  • Gumbel distribution
  • Kardar-Parisi-Zhang universality class
  • Markov models and/or hidden Markov models
  • Pairwise sequence alignment
  • Statistical significance
  • Statistics of motifs or strings

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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