Improved algorithms for DNA sequence alignment and revision of scoring matrix

Sequence alignment is the procedure of comparing two (pair-wise alignment) or more (multiple sequence alignment) sequences by searching for a series of individual characters or character patterns that are in the same order in the sequences. Classical methods like Needleman-Wunsch (for global alignment) and Smith-Waterman (for local alignment) suffer from the drawback that it involves a large number of computational steps and has to statically allocate a large section of memory for computer implementation. Moreover the PAM matrix used as a scoring scheme for sequence comparison is unsuitable when we are considering only a few of the total 20 amino acids. In this paper, we propose alternate methods to obtain global and local alignment between two sequences using direct comparison and compare the performance of our algorithms with that of the classical method. We also propose an alternate scoring scheme based on fuzzy concept and discuss its advantage over conventional PAM matrix.