Multiple sequence alignment with genetic algorithms

Authors:
Marco Botta;Guido Negro
Affiliations:
Dipartimento di Informatica, University of Torino, Torino, Italy and Center for Complex Systems in Molecular Biology and Medicine, University of Torino, Torino, Italy;Dipartimento di Informatica, University of Torino, Torino, Italy
Venue:
CIBB'09 Proceedings of the 6th international conference on Computational intelligence methods for bioinformatics and biostatistics
Year:
2009

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Multiple Sequence Alignment Using Parallel Genetic Algorithms

SEAL'98 Selected papers from the Second Asia-Pacific Conference on Simulated Evolution and Learning on Simulated Evolution and Learning

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Abstract

The multiple sequence alignment problem is one the most common task in the analysis of sequential data, especially in bioinformatics. In this paper, we propose to use a genetic algorithm to compute a multiple sequence alignment, by optimizing a simple scoring function. Even though the idea of using genetic algorithms is not new, the presented approach differs in the representation of the multiple alignment and in the simplicity of the genetic operators. The results so far obtained are reported and discussed in this paper.