Faster and efficient algorithm for sequence alignment

Abstract

In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity if two sequences in an alignment share a common ancestor, mismatches can be interpreted as point mutations and gaps as indels. The goal of this paper is to explore the computational approaches to sequence alignment in a faster and optimal way. Two techniques that have been studied are global alignment and local alignment. In this paper, I have used the idea of both the alignment techniques separately. Each technique follows an algorithm (Needleman – Wunsch algorithm for global alignment and Smith – Waterman algorithm for local alignment) which helps in generating proper optimal alignment accordingly. Multiple DNA sequences are read and according to alignment type, the sequences are matched.