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dc.contributor.authorLiew, Alan Wee-Chungen_US
dc.contributor.authorLaw, Ngai-Fongen_US
dc.contributor.authorYan, Hongen_US
dc.date.accessioned2017-04-24T12:52:07Z
dc.date.available2017-04-24T12:52:07Z
dc.date.issued2011en_US
dc.date.modified2012-09-14T02:22:27Z
dc.identifier.issn18722156en_US
dc.identifier.doi10.2174/187221511796392097en_US
dc.identifier.urihttp://hdl.handle.net/10072/41027
dc.description.abstractIn DNA microarray experiments, discovering groups of genes that share similar transcriptional characteristics is instrumental in functional annotation, tissue classification and motif identification. However, in many situations a subset of genes only exhibits a consistent pattern over a subset of conditions. Although used extensively in gene expression data analysis, conventional clustering algorithms that consider the entire row or column in an expression matrix can therefore fail to detect useful patterns in the data. Recently, biclustering has been proposed as a powerful computational tool to detect subsets of genes that exhibit consistent pattern over subsets of conditions. In this article, we review several recent patents in bicluster analysis, and in particular, highlight a recent patent from our group about a novel geometric-based biclustering method that handles the class of bicluster patterns with linear coherent variation across the row and/or column dimension. This class of bicluster patterns is of particular importance since it subsumes all constant, additive, and multiplicative bicluster patterns normally used in gene expression.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.format.extent432222 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherBentham Science Publishers Ltd.en_US
dc.publisher.placeNetherlandsen_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofpagefrom117en_US
dc.relation.ispartofpageto125en_US
dc.relation.ispartofissue2en_US
dc.relation.ispartofjournalRecent Patents on DNA & Gene Sequencesen_US
dc.relation.ispartofvolume5en_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchPattern Recognition and Data Miningen_US
dc.subject.fieldofresearchcode080109en_US
dc.titleRecent Patents on Biclustering Algorithms for Gene Expression Data Analysisen_US
dc.typeJournal articleen_US
dc.type.descriptionC1 - Peer Reviewed (HERDC)en_US
dc.type.codeC - Journal Articlesen_US
gro.facultyGriffith Sciences, School of Information and Communication Technologyen_US
gro.rights.copyrightCopyright 2011 Bentham Science Publishers. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal website for access to the definitive, published version.en_US
gro.date.issued2011
gro.hasfulltextFull Text


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