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dc.contributor.authorTamjidul Hoque, Md.
dc.contributor.authorChetty, Madhu
dc.contributor.authorS. Dooley, Laurence
dc.date.accessioned2017-05-03T16:59:15Z
dc.date.available2017-05-03T16:59:15Z
dc.date.issued2005
dc.date.modified2010-02-09T05:28:57Z
dc.identifier.issn9783540296744
dc.identifier.doi10.1007/11573067_35
dc.identifier.urihttp://hdl.handle.net/10072/28693
dc.description.abstractThe use of Genetic Algorithms in a 2D Hydrophobic-Hydrophilic (HP) model in protein folding prediction application requires frequent fitness function computations. While the fitness computation is linear, the overhead incurred is significant with respect to the protein folding prediction problem. Any reduction in the computational cost will therefore assist in more efficiently searching the enormous solution space for protein folding prediction. This paper proposes a novel pruning strategy that exploits the inherent properties of the HP model and guarantee reduction of the computational complexity during an ordered traversal of the amino acid chain sequences for fitness computation, truncating the sequence by at least one residue.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSpringer
dc.publisher.placeGermany
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom346
dc.relation.ispartofpageto354
dc.relation.ispartofjournalLecture Notes in Computer Science
dc.relation.ispartofvolume3745
dc.rights.retentionY
dc.subject.fieldofresearchBioinformatics
dc.subject.fieldofresearchcode060102
dc.titleEfficient Computation of Fitness Function by Pruning in Hydrophobic-Hydrophilic Model
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.date.issued2005
gro.hasfulltextNo Full Text
gro.griffith.authorHoque, Md T.


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