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dc.contributor.authorWu, Shuanhuen_US
dc.contributor.authorXie, Xudongen_US
dc.contributor.authorLiew, Alan Wee-Chungen_US
dc.contributor.authorYan, Hongen_US
dc.date.accessioned2017-04-24T12:52:38Z
dc.date.available2017-04-24T12:52:38Z
dc.date.issued2007en_US
dc.date.modified2009-10-16T05:20:44Z
dc.identifier.issn15393755en_US
dc.identifier.doi10.1103/PhysRevE.75.041908en_AU
dc.identifier.urihttp://hdl.handle.net/10072/17081
dc.description.abstractThe eukaryotic promoter prediction is one of the most important problems in DNA sequence analysis, but also a very difficult one. Although a number of algorithms have been proposed, their performances are still limited by low sensitivities and high false positives. We present a method for improving the performance of promoter regions prediction. We focus on the selection of most effective features for different functional regions in DNA sequences. Our feature selection algorithm is based on relative entropy or Kullback-Leibler divergence, and a system combined with position-specific information for promoter regions prediction is developed. The results of testing on large genomic sequences and comparisons with the PromoterInspector and Dragon Promoter Finder show that our algorithm is efficient with higher sensitivity and specificity in predicting promoter regions.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherAmerican Physical Societyen_US
dc.publisher.placeUnited Statesen_US
dc.publisher.urihttp://pre.aps.org/en_AU
dc.relation.ispartofstudentpublicationNen_AU
dc.relation.ispartofpagefrom041908-1en_US
dc.relation.ispartofpageto041908-7en_US
dc.relation.ispartofissue4en_US
dc.relation.ispartofjournalPhysical Review E (Statistical, Nonlinear, and Soft Matter Physics)en_US
dc.relation.ispartofvolume75en_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchcode280207en_US
dc.subject.fieldofresearchcode270202en_US
dc.titleEukaryotic promoter prediction based on relative entropy and positional informationen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.date.issued2007
gro.hasfulltextNo Full Text


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