Enhancing N-Gram-Hirschberg Algorithm by Using Hash Function

Abstract

Dynamic programming-based algorithm such as Smith-Waterman algorithm, which produces the most optimal result, has been known as one of the most used algorithm for sequence alignment. Hirschberg algorithm is the space saving version of Smith-Waterman algorithm. However, both algorithms are still very computational intensive. The N-Gram-Hirschberg algorithm is introduced to further reduced the space requirement and at the same time, to speed up the sequences alignment algorithm. This research aims to enhance the N-Gram-Hirschberg algorithm by embedding the Hashing function, adopted from an exact string matching algorithm called Karp-Rabin. The hash function is used to enhance the transformation process for the algorithm. The new method improves the processing time of the N-Gram-Hirschberg without sacrificing the quality of the output. The best time enhancement we got was when word length is two for protein sequence length ranges between 100-1000.