A Hybridization of Artificial Bee Colony with Swarming Approach of Bacterial Foraging Optimization for Multiple Sequence Alignment

A key and a primary phase for performing additional successive responsibilities in bioinformatics such as critical residue identification, conserved motif findings, phylogenetic analysis, predicting the secondary structure of protein, protein function prediction, the classification of proteins, and much more can be done by aligning multiple protein sequences termed as multiple sequence alignment (MSA). As a result of this, MSA expands as a vast active research field in bioinformatics. Generally, MSA is the process of aligning three or more sequences of DNA/nucleotides simultaneously. Nowadays the number of sequences in databases is increasing expeditiously. Due to this, many methods aroused drastically to implement the MSA problem within few years. Miserably it is an NP-complete problem, still the biologically perfect alignment methods are difficult to find. The objective of this chapter is to shed light on various recent techniques used to solve MSA. And also, a hybridization of artificial bee colony with swarming approach of bacterial foraging optimization (ABC-BFO) algorithm has been proposed to solve the MSA problem with better objective values, which leads to identify the biological features.

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