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Fast Dynamic Algorithm for Sequence Alignment Based On Bioinformatics

by Sara A.Shehab, Arabi Keshk, Hany Mahgoub
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 37 - Number 7
Year of Publication: 2012
Authors: Sara A.Shehab, Arabi Keshk, Hany Mahgoub
10.5120/4624-6636

Sara A.Shehab, Arabi Keshk, Hany Mahgoub . Fast Dynamic Algorithm for Sequence Alignment Based On Bioinformatics. International Journal of Computer Applications. 37, 7 ( January 2012), 54-61. DOI=10.5120/4624-6636

@article{ 10.5120/4624-6636,
author = { Sara A.Shehab, Arabi Keshk, Hany Mahgoub },
title = { Fast Dynamic Algorithm for Sequence Alignment Based On Bioinformatics },
journal = { International Journal of Computer Applications },
issue_date = { January 2012 },
volume = { 37 },
number = { 7 },
month = { January },
year = { 2012 },
issn = { 0975-8887 },
pages = { 54-61 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume37/number7/4624-6636/ },
doi = { 10.5120/4624-6636 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:23:45.026295+05:30
%A Sara A.Shehab
%A Arabi Keshk
%A Hany Mahgoub
%T Fast Dynamic Algorithm for Sequence Alignment Based On Bioinformatics
%J International Journal of Computer Applications
%@ 0975-8887
%V 37
%N 7
%P 54-61
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Sequence alignment is widely used in Bioinformatics for Genome Sequence difference identification. It is the main problem of computational biology. Any sequence of Deoxyribonucleic acid (DNA), Ribonucleic acid (RNA), and protein can be alignment by many algorithms called bioinformatics algorithms. This paper presents a new implemented algorithm for sequence alignment based on concepts from bioinformatics algorithms .The implemented algorithm is called fast dynamic algorithm for sequence alignment (FDASA). This implemented algorithm based on making a matrix of M×N (M is the length of the first sequence, N is the length of the second sequence), After that filling the three main diagonal without filling the unused data and at the same time get the optimal solution; so that the execution time is decreased, the performance is high and the memory location decreased. The implementation introduced in this paper made a comparison between the dynamic algorithms Needleman-Wunsch algorithm, Smith-Waterman and our algorithm FDASA to test the execution time. The results show that our algorithm FDASA decreased the execution time when compared with Needleman-Wunsch and Smith-Waterman algorithms.

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Index Terms

Computer Science
Information Sciences

Keywords

computational biology FDASA Sequence DNA RNA dynamic algorithms Needleman-Wunsch Smith-Waterman

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