### 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 language | English |
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Title of host publication | Combinatorial Pattern Matching - 11th Annual Symposium, CPM 2000, Proceedings |

Editors | David Sankoff, Raffaele Giancarlo |

Publisher | Springer Verlag |

Pages | 84-98 |

Number of pages | 15 |

ISBN (Electronic) | 3540676333, 9783540676331 |

Publication status | Published - 2000 Jan 1 |

Event | 11th Annual Symposium on Combinatorial Pattern Matching, CPM 2000 - Montreal, Canada Duration: 2000 Jun 21 → 2000 Jun 23 |

### Publication series

Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 1848 |

ISSN (Print) | 0302-9743 |

ISSN (Electronic) | 1611-3349 |

### Other

Other | 11th Annual Symposium on Combinatorial Pattern Matching, CPM 2000 |
---|---|

Country | Canada |

City | Montreal |

Period | 00-06-21 → 00-06-23 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Theoretical Computer Science
- Computer Science(all)

### Cite this

*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.

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*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.** / Horton, Paul.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Tsukuba BB

T2 - A branch and bound algorithm for local multiple sequence alignment

AU - Horton, Paul

PY - 2000/1/1

Y1 - 2000/1/1

N2 - 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.

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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UR - http://www.scopus.com/inward/citedby.url?scp=84937402994&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84937402994

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 84

EP - 98

BT - Combinatorial Pattern Matching - 11th Annual Symposium, CPM 2000, Proceedings

A2 - Sankoff, David

A2 - Giancarlo, Raffaele

PB - Springer Verlag

ER -