|International Journal of Computer Applications
|Foundation of Computer Science (FCS), NY, USA
|Volume 57 - Number 22
|Year of Publication: 2012
|Authors: Arabi E. Keshk, Mohammed Ossman, Lamiaa Fathi Hussein
Arabi E. Keshk, Mohammed Ossman, Lamiaa Fathi Hussein . Fast Longest Common Subsequences for Bioinformatics Dynamic Programming. International Journal of Computer Applications. 57, 22 ( November 2012), 12-18. DOI=10.5120/9419-3569
Bioinformatics applications represent an increasingly important workload to improve the programs of sequence analysis. It can be used to assign function to genes and proteins by the study of the similarities between the compared sequences. This paper introduces a modified implementation of bioinformatics algorithm for sequence alignment . The implemented algorithm is called Fast Longest Common Subsequence (FLCS). It is filling the three main diagonals without filling the entire matrix by the unused data. It gets the optimal solution but the execution time is decreased and the performance is high. To illustrate the effectiveness of optimizing the performance of the proposed FLCS algorithm and demonstrate its superiority, it is compared with Needleman-Wunsch, Smith-Waterman and Longest Common Subsequence algorithms.