Toward efficient mutliple molecular sequence alignment: A system of genetic algorithm and dynamic programming

Toward efficient mutliple molecular sequence alignment: A system of genetic algorithm and dynamic programming

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Article ID: iaor1999695
Country: United States
Volume: 27
Issue: 6
Start Page Number: 918
End Page Number: 932
Publication Date: Jun 1997
Journal: IEEE Transactions On Systems, Man and Cybernetics
Authors: ,
Keywords: programming: dynamic, programming: nonlinear
Abstract:

Multiple biomolecular sequence alignment is among the most important and challenging tasks in computational biology. It is characterized by great complexity in processing time. In this paper, a multiple-sequence alignment system is reported which combines the techniques of genetic algorithms and pairwise dynamic programming. Genetic algorithms are stochastic approaches for efficient and robust search. By converting biomolecular sequence alignment into a problem of searching for an optimal or a near-optimal point in a solution space, a genetic algorithm is used to find match blocks very efficiently. A pairwise dynamic programming is then applied, to the sub-sequences between the match blocks. Combining the strengths of the two methods, the system achieves high efficiency and high alignment quality. In this paper, the system is described in detail. The system's performance is analyzed and the experimental results are presented.

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