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Fast Longest Common Subsequences for Bioinformatics Dynamic Programming

by Arabi E. Keshk, Mohammed Ossman, Lamiaa Fathi Hussein
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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
10.5120/9419-3569

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

@article{ 10.5120/9419-3569,
author = { Arabi E. Keshk, Mohammed Ossman, Lamiaa Fathi Hussein },
title = { Fast Longest Common Subsequences for Bioinformatics Dynamic Programming },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 57 },
number = { 22 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 12-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume57/number22/9419-3569/ },
doi = { 10.5120/9419-3569 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:01:06.359298+05:30
%A Arabi E. Keshk
%A Mohammed Ossman
%A Lamiaa Fathi Hussein
%T Fast Longest Common Subsequences for Bioinformatics Dynamic Programming
%J International Journal of Computer Applications
%@ 0975-8887
%V 57
%N 22
%P 12-18
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

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.

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Index Terms

Computer Science
Information Sciences

Keywords

computational biology algorithm Expressed Sequence Tag heuristic algorithms BLAST FASTA dynamic algorithms Needleman-Wunsch Smith-Waterman LCS

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