Bacterial Foraging Optimization –Genetic Algorithm for Multiple Sequence Alignment with Multi-Objectives

Abstract

This research work focus on the multiple sequence alignment, as developing an exact multiple sequence alignment for different protein sequences is a difficult computational task. In this research, a hybrid algorithm named Bacterial Foraging Optimization-Genetic Algorithm (BFO-GA) algorithm is aimed to improve the multi-objectives and carrying out measures of multiple sequence alignment. The proposed algorithm employs multi-objectives such as variable gap penalty minimization, maximization of similarity and non-gap percentage. The proposed BFO-GA algorithm is measured with various MSA methods such as T-Coffee, Clustal Omega, Muscle, K-Align, MAFFT, GA, ACO, ABC and PSO. The experiments were taken on four benchmark datasets such as BAliBASE 3.0, Prefab 4.0, SABmark 1.65 and Oxbench 1.3 databases and the outcomes prove that the proposed BFO-GA algorithm obtains better statistical significance results as compared with the other well-known methods. This research study also evaluates the practicability of the alignments of BFO-GA by applying the optimal sequence to predict the phylogenetic tree by using ClustalW2 Phylogeny tool and compare with the existing algorithms by using the Robinson-Foulds (RF) distance performance metric. Lastly, the statistical implication of the proposed algorithm is computed by using the Wilcoxon Matched-Pair Signed-Rank test and also it infers better results.In Bioinformatics, the sequence alignments are used to show evolutionary relationships by constructing phylogenetic trees. Sequence alignment and phylogenetic analysis are strongly related due to measuring the relatedness of homologous sequence. Generally the protein sequence consists of amino acids, which are linked with each other. Sequence alignment describes the mode of arrangement of protein sequence, in order to distinguish the areas of similarity among them 1 . Aligning refers to matching as many characters as possible from each sequence. Primarily, the sequence alignment is applied to infer functional, morphological and evolutionary relationship between the protein sequences. The alignment of the sequence is used to find similarity level between the query sequence and different database sequences.Today, there are several sequence alignment techniques are available and this research study concentrates on the multiple sequence alignment. One of the fundamental problems in computational biology is the alignment of multiple sequences of DNA/Protein. The computational approaches which are used to align the Protein/ DNA sequences generally falls into two categories: global and local alignments 2 . The multiple sequence alignment comes under the category of global alignment and it's an adjacent of pairwise alignment to incorporate more than two sequences at a time. Various methods have been implemented on MSA, but these approaches add up under three major classes such as: dynamic programming, Progressive and Iterative methods. In this research work the proposed BFO-GA algorithm comes under the category of Iterative -Progressive method...

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