Article

A hybrid genetic search for multiple sequence alignment

Authors:

Seung-Hyun Moon,

Sung-Soon Choi,

Byung-Ro MoonAuthors Info & Claims

GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation

Pages 303 - 304

https://doi.org/10.1145/1143997.1144051

Published: 08 July 2006 Publication History

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Abstract

This paper proposes a hybrid genetic algorithm for multiple sequence alignment. The algorithm evolves guide sequences and aligns input sequences based on the guide sequences. It also embeds a local search heuristic to search the problem space effectively. In the experiments for various data sets, the proposed algorithm showed the performance comparable to existing algorithms.

References

[1]

D. Gusfield. Efficient methods for multiple sequence alignment with guaranteed error bounds. Bull. Math. Biol., 55(1):141--154, 1993.

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[2]

C. Shyu, L. Sheneman, and J. A. Foster. Multiple sequence alignment with evolutionary computation. Genetic Programming and Evolvable Machines, 5(2):121--144, 2004.

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A hybrid genetic search for multiple sequence alignment
1. Applied computing
  1. Life and medical sciences
2. Theory of computation
  1. Design and analysis of algorithms
    1. Data structures design and analysis
      1. Sorting and searching

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Information & Contributors

Information

Published In

GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation

July 2006

2004 pages

ISBN:1595931864

DOI:10.1145/1143997

General Chair:
Mike Cattolico
Tiger Mountain Scientific, Inc., USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 July 2006

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GECCO06

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GECCO06: Genetic and Evolutionary Computation Conference

July 8 - 12, 2006

Washington, Seattle, USA

Acceptance Rates

GECCO '06 Paper Acceptance Rate 205 of 446 submissions, 46%;

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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