Binary Particle Swarm Optimization Algorithm with Mutation for Multiple Sequence Alignment.
Multiple sequence alignment (MSA) is a fundamental and challenging problem in the analysis of biologic sequence. The MSA problem is hard to be solved directly, for it always results in exponential complexity with the scale of the problem. In this paper, we propose mutation-based binary particle swar...
| Publicado en: | Biology Forum / Rivista di Biologia Vol. 102; no. 1; pp. 75 - 95 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Fabrizio Serra Editore
2009
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=43205687&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 43205687 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 18256538 M1F jtl: Biology Forum / Rivista di Biologia issn: 18256538 maglogo: N pubinfo: dt: 2009 vid: 102 iid: 1 pid: 50689 pub: Fabrizio Serra Editore artinfo: ui: 43205687 ppf: 75 ppct: 20 formats: fmt: @attributes: type: P size: 686KB tig: atl: Binary Particle Swarm Optimization Algorithm with Mutation for Multiple Sequence Alignment. aug: au: Hai-Xia Long Wen-Bo Xu Jun Sun affil: School of Information Technology, Jiangnan University, No. 1800, Lihudadao Road, Wuxi, Jiangsu 214122, China su: Particle swarm optimization Genetic algorithms Nucleotide sequence Genetic mutation Computational biology Convergent evolution sug: subj: Particle swarm optimization Genetic algorithms Nucleotide sequence Genetic mutation Computational biology Convergent evolution keyword: Amino acids Binary particle swarm optimization Multiple sequence alignment Mutation Nucleic acid ab: Multiple sequence alignment (MSA) is a fundamental and challenging problem in the analysis of biologic sequence. The MSA problem is hard to be solved directly, for it always results in exponential complexity with the scale of the problem. In this paper, we propose mutation-based binary particle swarm optimization (M-BPSO) for MSA solving. In the proposed M-BPSO algorithm, BPSO algorithm is conducted to provide alignments. Thereafter, mutation operator is performed to move out of local optima and speed up convergence. From simulation results of nucleic acid and amino acid sequences, it is shown that the proposed M-BPSO algorithm has superior performance when compared to other existing algorithms. Furthermore, this algorithm can be used quickly and efficiently for smaller and medium size sequences. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Biology Forum / Rivista di Biologia is the property of Fabrizio Serra Editore and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Biology Forum / Rivista di Biologia holder: Fabrizio Serra Editore dt: @attributes: year: 2009 holdings: @attributes: islocal: N |
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