期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2015
期号：NCETAS
页码：50
出版社：S&S Publications
摘要：Multiple Sequence Alignment is a well known and computationally one of the most challenging problemin the field of molecular biology. It takes a major role in the domain of molecular sequence analysis. An alignment isbasically the arrangement of two (pair-wise alignments) or more (multiple alignments) sequences of „residues‟ (i.e.amino acids or nucleotides) that maximizes the similarities among them. In algorithm, the problem basically consists ofopening and extending gaps in the multiple sequences. The goal is to maximize an objective function (measurement ofsimilarity). In the recent past, Genetic Algorithm (GA) based solutions have emerged as useful tool for solving MSAproblem. Genetic algorithms - a well known category of evolutionary algorithms are well suited for various problems ofthis nature because gaps and residues are discrete units. This paper proposes an elitist solution using genetic algorithmfor determining alignment of multiple sequences. Different genetic operators like crossover rate, mutation rate etc. can bespecified by the user. Results have been recorded depending upon observations & experiments w.r.t variable parameterslike variable number of generations vs. fixed population size & vice versa, variable mutation & crossover rates. Thedatasets have been chosen from the BAliBASE standard benchmark alignment suite for experimental work & analysis.
