Web Reference: The algorithm was first proposed by Temple F. Smith and Michael S. Waterman in 1981. [1] Like the Needleman–Wunsch algorithm, of which it is a variation, Smith–Waterman is a dynamic programming algorithm. The Smith-Waterman algorithm is a dynamic programming method for finding the optimal local alignment between two sequences. Unlike global alignment, it identifies the best matching subsequences, making it ideal for finding similar regions in otherwise divergent sequences. Dynamic programming is used for optimal alignment of two sequences. It finds the alignment in a more quantitative way by giving some scores for matches and mismatches (Scoring matrices), rather than only applying dots.
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