Optimizing Genetic Algorithm Parameters for Multiple Sequence Alignment Based on Structural Information

Abstract

Multiple sequence alignments (MSAs) are commonly used approaches in the analysis of sequence structure relationships. MSA is generally the alignment of three or more protein or nucleic acid sequences that maximises the similarities between sequences. In this paper, we use genetic algorithm to compute multiple sequence alignment using the structural information as the scoring scheme implemented in the program Multiobjective Optimizer for Sequence Alignments based on Structural Evaluations (MOSAStrE). We performed numerical experiments on datasets obtained from benchmark alignment database (BAliBASE) to solve multiple sequence alignment. To test the performance of the proposed algorithm, numerical simulations were carried out in deciding the appropriate set of parameter values for the