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Reseach Article

Residue Number System: An Important Application in Bioinformatics

by Hassan Kehinde Bello, Kazeem Alagbe Gbolagade
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 10
Year of Publication: 2018
Authors: Hassan Kehinde Bello, Kazeem Alagbe Gbolagade
10.5120/ijca2018916106

Hassan Kehinde Bello, Kazeem Alagbe Gbolagade . Residue Number System: An Important Application in Bioinformatics. International Journal of Computer Applications. 179, 10 ( Jan 2018), 28-33. DOI=10.5120/ijca2018916106

@article{ 10.5120/ijca2018916106,
author = { Hassan Kehinde Bello, Kazeem Alagbe Gbolagade },
title = { Residue Number System: An Important Application in Bioinformatics },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2018 },
volume = { 179 },
number = { 10 },
month = { Jan },
year = { 2018 },
issn = { 0975-8887 },
pages = { 28-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number10/28838-2018916106/ },
doi = { 10.5120/ijca2018916106 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:54:59.801008+05:30
%A Hassan Kehinde Bello
%A Kazeem Alagbe Gbolagade
%T Residue Number System: An Important Application in Bioinformatics
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 10
%P 28-33
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents an overview and comprehensive survey of Residue Number System (RNS) and Bioinformatics. It focuses on application of RNS to Smith-Waterman Algorithm (SWA), highlights how the inherent attributes of RNS can be applied to improve performance of SWA in the analysis of Deoxyribonucleic Acid (DNA) and also observes the two principal methods of data conversion and lastly, we suggest the direction for future research.

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Index Terms

Computer Science
Information Sciences

Keywords

Residue Number System Smith-Waterman Algorithm Deoxyribonucleic Acid Bioinformatics.