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A Hybrid Genetic Algorithm for RNA Structural Alignment

by Abdesslem Layeb, Imen Bensetira, Kenza Bouaroudj
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 19 - Number 7
Year of Publication: 2011
Authors: Abdesslem Layeb, Imen Bensetira, Kenza Bouaroudj
10.5120/2370-3120

Abdesslem Layeb, Imen Bensetira, Kenza Bouaroudj . A Hybrid Genetic Algorithm for RNA Structural Alignment. International Journal of Computer Applications. 19, 7 ( April 2011), 41-47. DOI=10.5120/2370-3120

@article{ 10.5120/2370-3120,
author = { Abdesslem Layeb, Imen Bensetira, Kenza Bouaroudj },
title = { A Hybrid Genetic Algorithm for RNA Structural Alignment },
journal = { International Journal of Computer Applications },
issue_date = { April 2011 },
volume = { 19 },
number = { 7 },
month = { April },
year = { 2011 },
issn = { 0975-8887 },
pages = { 41-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume19/number7/2370-3120/ },
doi = { 10.5120/2370-3120 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:06:24.369271+05:30
%A Abdesslem Layeb
%A Imen Bensetira
%A Kenza Bouaroudj
%T A Hybrid Genetic Algorithm for RNA Structural Alignment
%J International Journal of Computer Applications
%@ 0975-8887
%V 19
%N 7
%P 41-47
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The RNA structural alignment is one of the most challenging tasks in bioinformatics. However, finding the accurate conserved structure of a set of RNA sequences is still being a difficult task. In this work, the problem is cast as an optimization problem for which a new framework relaying on hybrid genetic algorithm is proposed. The contribution consists in using a new objective function based on the Structure Conservation Index (SCI). In order to enhance the Genetic Algorithms (GA) performances, a Simulated Annealing (SA) procedure has been used. The proposed algorithm is composed on two phases.The first phase consists of applying a genetic algorithm.In the second phase, the simulated annealing procedure is applied in order to improve the final population given by the genetic algorithm. Experiments on a wide range of data sets have shown the effectiveness of the proposed framework and its ability to achieve good quality solutions comparing to those given by others techniques.

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Index Terms

Computer Science
Information Sciences

Keywords

RNA Structure Prediction Genetic Algorithm Simulated Annealing Structure Conservation Index

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