Tsukuba BB

A branch and bound algorithm for local multiple sequence alignment

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

2 Citations (Scopus)

Abstract

In this paper we present a branch and bound algorithm for local gapless multiple sequence alignment (motif alignment) and its implementation. This is the first program to exploit the fact that the motif alignment problem is easier for short motifs. Indeed for a fixed motif width the running time of the algorithm is asymptotically linear in the size of the input. We tested the performance of the program on a dataset of 300 E.coli promoter sequences. For a motif width of 4 the optimal alignment of the entire set of sequences can be found. For the more natural motif width of 6 the program can align 19 sequences of length 100; more than twice the number of sequences which can be aligned by the best previous exact algorithm. The algorithm can relax the constraint of requiring each sequence to be aligned, and align 100 of the 300 promoter sequences with a motif width of 6. We also compare the effectiveness of the Gibbs sampling and beam search heuristics on this problem and show that in some cases our branch and bound algorithm can find the optimal solution, with proof of optimality, when those heuristics fail to find the optimal solution.

Original languageEnglish
Title of host publicationCombinatorial Pattern Matching - 11th Annual Symposium, CPM 2000, Proceedings
EditorsDavid Sankoff, Raffaele Giancarlo
PublisherSpringer Verlag
Pages84-98
Number of pages15
ISBN (Electronic)3540676333, 9783540676331
Publication statusPublished - 2000 Jan 1
Event11th Annual Symposium on Combinatorial Pattern Matching, CPM 2000 - Montreal, Canada
Duration: 2000 Jun 212000 Jun 23

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1848
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th Annual Symposium on Combinatorial Pattern Matching, CPM 2000
CountryCanada
CityMontreal
Period00-06-2100-06-23

Fingerprint

Multiple Sequence Alignment
Branch and Bound Algorithm
Alignment
Promoter
Optimal Solution
Heuristics
Beam Search
Asymptotically Linear
Gibbs Sampling
Escherichia coli
Exact Algorithms
Escherichia Coli
Optimality
Sampling
Entire

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Paul, B. H. I. (2000). Tsukuba BB: A branch and bound algorithm for local multiple sequence alignment. In D. Sankoff, & R. Giancarlo (Eds.), Combinatorial Pattern Matching - 11th Annual Symposium, CPM 2000, Proceedings (pp. 84-98). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1848). Springer Verlag.
Paul, Brice Horton Ii. / Tsukuba BB : A branch and bound algorithm for local multiple sequence alignment. Combinatorial Pattern Matching - 11th Annual Symposium, CPM 2000, Proceedings. editor / David Sankoff ; Raffaele Giancarlo. Springer Verlag, 2000. pp. 84-98 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Paul, BHI 2000, Tsukuba BB: A branch and bound algorithm for local multiple sequence alignment. in D Sankoff & R Giancarlo (eds), Combinatorial Pattern Matching - 11th Annual Symposium, CPM 2000, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1848, Springer Verlag, pp. 84-98, 11th Annual Symposium on Combinatorial Pattern Matching, CPM 2000, Montreal, Canada, 00-06-21.

Tsukuba BB : A branch and bound algorithm for local multiple sequence alignment. / Paul, Brice Horton Ii.

Combinatorial Pattern Matching - 11th Annual Symposium, CPM 2000, Proceedings. ed. / David Sankoff; Raffaele Giancarlo. Springer Verlag, 2000. p. 84-98 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1848).

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

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AB - In this paper we present a branch and bound algorithm for local gapless multiple sequence alignment (motif alignment) and its implementation. This is the first program to exploit the fact that the motif alignment problem is easier for short motifs. Indeed for a fixed motif width the running time of the algorithm is asymptotically linear in the size of the input. We tested the performance of the program on a dataset of 300 E.coli promoter sequences. For a motif width of 4 the optimal alignment of the entire set of sequences can be found. For the more natural motif width of 6 the program can align 19 sequences of length 100; more than twice the number of sequences which can be aligned by the best previous exact algorithm. The algorithm can relax the constraint of requiring each sequence to be aligned, and align 100 of the 300 promoter sequences with a motif width of 6. We also compare the effectiveness of the Gibbs sampling and beam search heuristics on this problem and show that in some cases our branch and bound algorithm can find the optimal solution, with proof of optimality, when those heuristics fail to find the optimal solution.

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Paul BHI. Tsukuba BB: A branch and bound algorithm for local multiple sequence alignment. In Sankoff D, Giancarlo R, editors, Combinatorial Pattern Matching - 11th Annual Symposium, CPM 2000, Proceedings. Springer Verlag. 2000. p. 84-98. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).