Aligning two molecular sequences using genetic operators in grey wolf optimiser technique
by J. Jayapriya; Michael Arock
International Journal of Data Mining and Bioinformatics (IJDMB), Vol. 15, No. 4, 2016

Abstract: Sequence analysis is one of the most important concepts in the domain of bioinformatics. Molecular sequence alignment is a predominant problem in sequence analysis. In this paper, we proposed a new approach for pairwise sequence alignment using a recent meta-heuristic algorithm called Grey Wolf Optimiser (GWO) technique in which genetic operators are integrated to yield efficient solutions. This algorithm obtains the initial set of alignments by inserting gaps randomly and uses the search agents in GWO for exploration and exploitation. In addition to this, genetic operators like crossover and mutation are applied for faster convergence. A novel horizontal crossover and a single-point crossover that suits, particularly for sequence alignment problem, are employed in this paper. Here, two mutations are used depending upon their threshold value. This threshold value depends on a novel fitness function F_F, which gives maximum matched counts for a new representation of the molecular sequences. When the F_F of the sequence is less than the threshold value, the global gap swap mutation is used and if it is greater, then aligned block gap swap mutation is employed. The results are compared with the state-of-the-art techniques and statistical evaluation done to prove that the proposed algorithm yields better solution.

Online publication date: Thu, 04-Aug-2016

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