Efficient Mining Algorithm for Protein Sequence Alignment

Abstract

Bioinformatics is the study and application of computational methods to life sciences data and the application of information technology to store, organize and analyze the vast amount of biological data. Protein sequence alignment is one of the crucial tasks of computational biology which forms the basis of many other tasks like protein structure prediction, protein function prediction and phylogenetic analysis. Alignment algorithms are needed to compare two or more sequences. Pairwise sequence alignment is concerned with comparing two Protein or DNA sequences - finding the global and local “optimum alignment” of the two sequences. Multiple sequence alignment (MSA) is a key step in elucidating evolutionary relationships, annotating newly sequenced segments, and understanding the relationship between biological sequences. So, pairwise alignment algorithm for protein sequences is proposed. Genetic algorithm with Bi-Directional Extension (BIDE), an efficient algorithm for mining frequent closed sequences, is used for multiple sequence alignment.