Abstract
Multiple sequence alignment (MSA) has become an important issue in computational molecular biology. The purpose of MSA is to infer evolutionary history or discover homologous regions among closely related DNA or protein sequences. A wide variety of approaches has been proposed for the MSA problem; however, some of them need prerequisites to find the best alignment or may suffer from the drawbacks of high computational complexity and huge memory requirement so they can be only applied to cases with a limited number of sequences. In this paper, we view the MSA problem as an optimization problem and resolve it by applying a genetic algorithm. In order to improve the search performance and obtain a better alignment quality, we design a few problem-specific genetic operators. Experimental results on real DNA and protein sequences are given to illustrate the feasibility of the proposed approach.
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