An improved model for statistical alignment

István Miklós, Zoltán Toroczkai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

The statistical approach to molecular sequence evolution involves the stochastic modeling of the substitution, insertion and deletion processes. Substitution has been modeled in a reliable way for more than three decades by using finite Markov-processes. Insertion and deletion, however, seem to be more difficult to model, and the recent approaches cannot acceptably deal with multiple insertions and deletions. A new method based on a generating function approach is introduced to describe the multiple insertion process. The presented algorithm computes the approximate joint probability of two sequences in O(l3) running time where l is the geometric mean of the sequence lengths.

Original languageEnglish
Title of host publicationAlgorithms in Bioinformatics - First International Workshop, WABI 2001 Århus Denmark, August 28-31, 2001 Proceedings
EditorsBernard M. E. Moret, Olivier Gascuel
PublisherSpringer Verlag
Pages1-10
Number of pages10
ISBN (Print)3540425160
DOIs
Publication statusPublished - Jan 1 2001
Event1st International Workshop on Algorithms in Bioinformatics, WABI 2001 - Arhus, Denmark
Duration: Aug 28 2001Aug 31 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2149
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Workshop on Algorithms in Bioinformatics, WABI 2001
CountryDenmark
CityArhus
Period8/28/018/31/01

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Miklós, I., & Toroczkai, Z. (2001). An improved model for statistical alignment. In B. M. E. Moret, & O. Gascuel (Eds.), Algorithms in Bioinformatics - First International Workshop, WABI 2001 Århus Denmark, August 28-31, 2001 Proceedings (pp. 1-10). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2149). Springer Verlag. https://doi.org/10.1007/3-540-44696-6_1