A practical approach to significance assessment in alignment with gaps

Nicholas Chia, Ralf Bundschuh

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


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
Issue number2
StatePublished - Mar 2006


  • 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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