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dc.contributor.authorHoque, Md Tamjidul
dc.contributor.authorChetty, Madhu
dc.contributor.authorLewis, Andrew
dc.contributor.authorSattar, Abdul
dc.date.accessioned2018-03-02T12:30:59Z
dc.date.available2018-03-02T12:30:59Z
dc.date.issued2011
dc.date.modified2011-06-16T06:01:50Z
dc.identifier.issn1545-5963
dc.identifier.doi10.1109/TCBB.2009.34
dc.identifier.urihttp://hdl.handle.net/10072/39141
dc.description.abstractThis paper presents the impact of twins and the measures for their removal from the population of genetic algorithm (GA) when applied to effective conformational searching. It is conclusively shown that a twin removal strategy for a GA provides considerably enhanced performance when investigating solutions to complex ab initio protein structure prediction (PSP) problems in low resolution model. Without twin removal, GA crossover and mutation operations can become ineffectual as generations lose their ability to produce significant differences which can lead to the solution stalling. The paper relaxes the definition of chromosomal twins in the removal strategy to not only encompass identical, but also highly-correlated chromosomes within the GA population, with empirical results consistently exhibiting significant improvements solving PSP problems.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent571316 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherIEEE
dc.publisher.placeUnited States
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom234
dc.relation.ispartofpageto245
dc.relation.ispartofissue1
dc.relation.ispartofjournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
dc.relation.ispartofvolume8
dc.rights.retentionY
dc.subject.fieldofresearchMathematical sciences
dc.subject.fieldofresearchBiological mathematics
dc.subject.fieldofresearchBiological sciences
dc.subject.fieldofresearchInformation and computing sciences
dc.subject.fieldofresearchcode49
dc.subject.fieldofresearchcode490102
dc.subject.fieldofresearchcode31
dc.subject.fieldofresearchcode46
dc.titleTwin Removal in Genetic Algorithms for Protein Structure Prediction Using Low-Resolution Model
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.facultyGriffith Sciences, School of Information and Communication Technology
gro.rights.copyright© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
gro.date.issued2011
gro.hasfulltextFull Text
gro.griffith.authorSattar, Abdul
gro.griffith.authorLewis, Andrew J.


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