An Improved Approach to Develop Global Alignment Algorithm and its Implementation by Making Software for Multiple Alignment, Phylogenetic Tree and GC Content

Abstract

Bioinformatics is the field of science in which biology, computer science, and information technology merge to form a single discipline. Bioinformatics deals with algorithms, databases and information systems, web technologies, artificial intelligence and soft computing, information and computation theory, software engineering, data mining, image processing, modelling and simulation, signal processing, discrete mathematics, control and system theory, circuit theory, and statistics, for generating new knowledge of biology and medicine, and improving & discovering new models of computation (e.g. DNA computing, neural computing, evolutionary computing, immuno-computing, swarm-computing, cellular-computing). In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. A large number of algorithms are used in bioinformatics such as global alignment, local alignment, multiple alignments etc. Global alignments, which attempt to align every residue in every sequence, are most useful when the sequences in the query set are similar and of roughly equal size. We worked with the global alignment algorithm with an improved and efficient manner. The improved algorithm is too much accurate for aligning the genome sequences with better computational time. And using this improved way we also developed the multiple alignment, phylogenetic tree and GC content of the sequences.