Multiple Sequence Alignment Using Parallel Genetic Algorithms

Authors:
L. A. Anbarasu;P. Narayanasamy;V. Sundararajan
Affiliations:
-;-;-
Venue:
SEAL'98 Selected papers from the Second Asia-Pacific Conference on Simulated Evolution and Learning on Simulated Evolution and Learning
Year:
1998

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Abstract

An efficient approach to solve multiple sequence alignment problem is presented in this paper. This approach is based on parallel genetic algorithm(PGA) that runs on a networked parallel environment. The algorithm optimizes an objective function 'weighted sums of pairs' which measures alignment quality. Using isolated independent subpopulations of alignments in a quasi evolutionary manner this approach gradually improves the fitness of the subpopulations as measured by an objective function. This parallel approach is shown to perform better than the sequential approach and an alternative method, clustalw. An investigation of the parameters of the algorithm further confirms the better performance.