Fragmented protein sequence alignment using two-layer particle swarm optimization (FTLPSO)

This paper presents a Fragmented protein sequence alignment using two-layer PSO (FTLPSO) method to overcome the drawbacks of particle swarm optimization (PSO) and improve its performance in solving multiple sequence alignment (MSA) problem. The standard PSO suffers from the trapping in local optima,...

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Main Authors: Nourelhuda Moustafa, Moustafa Elhosseini, Tarek Hosny Taha, Mofreh Salem
Format: Article
Language:English
Published: Elsevier 2017-04-01
Series:Journal of King Saud University: Science
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S1018364715301257
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spelling doaj-f250cf6ab64f454b8924845b21851a2b2020-11-25T01:08:04ZengElsevierJournal of King Saud University: Science1018-36472017-04-0129219120510.1016/j.jksus.2016.04.007Fragmented protein sequence alignment using two-layer particle swarm optimization (FTLPSO)Nourelhuda Moustafa0Moustafa Elhosseini1Tarek Hosny Taha2Mofreh Salem3Computers Engineering & Control Systems Dept., Mansoura University, P.O. box: 35516, EgyptComputers Engineering & Control Systems Dept., Mansoura University, P.O. box: 35516, EgyptCity for Scientific Research and Technology Applications, Environmental Biotechnology, P.O. box: 21934, New Borg El-Arab, EgyptComputers Engineering & Control Systems Dept., Mansoura University, P.O. box: 35516, EgyptThis paper presents a Fragmented protein sequence alignment using two-layer PSO (FTLPSO) method to overcome the drawbacks of particle swarm optimization (PSO) and improve its performance in solving multiple sequence alignment (MSA) problem. The standard PSO suffers from the trapping in local optima, and its disability to do better alignment for longer sequences. To overcome these problems, a fragmentation technique is first introduced to divide the longer datasets to a number of fragments. Then a two-layer PSO algorithm is applied to align each fragment, which has ability to deal with unconstrained optimization problems and increase diversity of particles. The proposed method is tested on some Balibase benchmarks of different lengths. The numerical results are compared with CLUSTAL Omega, CLUSTAL W2, TCOFFEE, KALIGN, and DIALIGN-PFAM. It has been shown that better alignment scores have been achieved using the proposed technique FTLPSO. Further, studies on PSO update equation’s parameters and the parameters of the used scoring functions are presented and discussed.http://www.sciencedirect.com/science/article/pii/S1018364715301257Multiple sequence alignmentParticle swarm optimizationFragmentationTwo-layer PSO
collection DOAJ
language English
format Article
sources DOAJ
author Nourelhuda Moustafa
Moustafa Elhosseini
Tarek Hosny Taha
Mofreh Salem
spellingShingle Nourelhuda Moustafa
Moustafa Elhosseini
Tarek Hosny Taha
Mofreh Salem
Fragmented protein sequence alignment using two-layer particle swarm optimization (FTLPSO)
Journal of King Saud University: Science
Multiple sequence alignment
Particle swarm optimization
Fragmentation
Two-layer PSO
author_facet Nourelhuda Moustafa
Moustafa Elhosseini
Tarek Hosny Taha
Mofreh Salem
author_sort Nourelhuda Moustafa
title Fragmented protein sequence alignment using two-layer particle swarm optimization (FTLPSO)
title_short Fragmented protein sequence alignment using two-layer particle swarm optimization (FTLPSO)
title_full Fragmented protein sequence alignment using two-layer particle swarm optimization (FTLPSO)
title_fullStr Fragmented protein sequence alignment using two-layer particle swarm optimization (FTLPSO)
title_full_unstemmed Fragmented protein sequence alignment using two-layer particle swarm optimization (FTLPSO)
title_sort fragmented protein sequence alignment using two-layer particle swarm optimization (ftlpso)
publisher Elsevier
series Journal of King Saud University: Science
issn 1018-3647
publishDate 2017-04-01
description This paper presents a Fragmented protein sequence alignment using two-layer PSO (FTLPSO) method to overcome the drawbacks of particle swarm optimization (PSO) and improve its performance in solving multiple sequence alignment (MSA) problem. The standard PSO suffers from the trapping in local optima, and its disability to do better alignment for longer sequences. To overcome these problems, a fragmentation technique is first introduced to divide the longer datasets to a number of fragments. Then a two-layer PSO algorithm is applied to align each fragment, which has ability to deal with unconstrained optimization problems and increase diversity of particles. The proposed method is tested on some Balibase benchmarks of different lengths. The numerical results are compared with CLUSTAL Omega, CLUSTAL W2, TCOFFEE, KALIGN, and DIALIGN-PFAM. It has been shown that better alignment scores have been achieved using the proposed technique FTLPSO. Further, studies on PSO update equation’s parameters and the parameters of the used scoring functions are presented and discussed.
topic Multiple sequence alignment
Particle swarm optimization
Fragmentation
Two-layer PSO
url http://www.sciencedirect.com/science/article/pii/S1018364715301257
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AT tarekhosnytaha fragmentedproteinsequencealignmentusingtwolayerparticleswarmoptimizationftlpso
AT mofrehsalem fragmentedproteinsequencealignmentusingtwolayerparticleswarmoptimizationftlpso
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