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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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 |
work_keys_str_mv |
AT nourelhudamoustafa fragmentedproteinsequencealignmentusingtwolayerparticleswarmoptimizationftlpso AT moustafaelhosseini fragmentedproteinsequencealignmentusingtwolayerparticleswarmoptimizationftlpso AT tarekhosnytaha fragmentedproteinsequencealignmentusingtwolayerparticleswarmoptimizationftlpso AT mofrehsalem fragmentedproteinsequencealignmentusingtwolayerparticleswarmoptimizationftlpso |
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1725184401193566208 |