GAPWA: genetic algorithm using pair wise alignment method for solving MSA problem
by Rohit Kumar Yadav; Haider Banka
International Journal of Convergence Computing (IJCONVC), Vol. 2, No. 2, 2016

Abstract: In bioinformatics, multiple sequence alignment is an NP-hard problem. Hence, bio-inspired techniques can be used to approximate the solution. In the current study, a hybrid genetic algorithm has been proposed to solve multiple sequence alignment problems i.e., termed as GAPWA. In which, two new mechanism have been proposed. First one is for initial population generation, and another for crossover and mutation operation. In the initial population generation, Needleman Wunsch pair wise method is adopted. In the second mechanism, modified crossover and mutation operation is used. In the performance analysis, GAPWA is compared with some of the well-known existing methods such as PRRP, DIALIGN, HMMT, SB-PIMA, GA, SAGA, and RBT-GA on a number of benchmark datasets from Bali-base 2.0. The obtained results show that the proposed approach GAPWA achieves better solutions compared to existing approaches in most of the cases.

Online publication date: Wed, 01-Feb-2017

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