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dc.contributor.authorZhao, Hongya
dc.contributor.authorLiew, Alan Wee-Chung
dc.contributor.authorXie, Xudong
dc.contributor.authorYan, Hong
dc.date.accessioned2017-05-03T15:20:41Z
dc.date.available2017-05-03T15:20:41Z
dc.date.issued2008
dc.date.modified2011-11-18T06:03:27Z
dc.identifier.issn0022-5193
dc.identifier.doi10.1016/j.jtbi.2007.11.030
dc.identifier.urihttp://hdl.handle.net/10072/22590
dc.description.abstractBiclustering is an important tool in microarray analysis when only a subset of genes co-regulates in a subset of conditions. Different from standard clustering analyses, biclustering performs simultaneous classification in both gene and condition directions in a microarray data matrix. However, the biclustering problem is inherently intractable and computationally complex. In this paper, we present a new biclustering algorithm based on the geometrical viewpoint of coherent gene expression profiles. In this method, we perform pattern identification based on the Hough transform in a column-pair space. The algorithm is especially suitable for the biclustering analysis of large-scale microarray data. Our studies show that the approach can discover significant biclusters with respect to the increased noise level and regulatory complexity. Furthermore, we also test the ability of our method to locate biologically verifiable biclusters within an annotated set of genes.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent601061 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherAcademic Press
dc.publisher.placeUnited Kingdom
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom264
dc.relation.ispartofpageto274
dc.relation.ispartofissue2
dc.relation.ispartofjournalJournal of Theoretical Biology
dc.relation.ispartofvolume251
dc.rights.retentionY
dc.subject.fieldofresearchMathematical sciences
dc.subject.fieldofresearchBiological sciences
dc.subject.fieldofresearchInformation and computing sciences
dc.subject.fieldofresearchcode49
dc.subject.fieldofresearchcode31
dc.subject.fieldofresearchcode46
dc.titleA new geometric biclustering algorithm based on the Hough transform for analysis of large-scale microarray data
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.rights.copyright© 2008 Elsevier Ltd. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
gro.date.issued2008
gro.hasfulltextFull Text
gro.griffith.authorLiew, Alan Wee-Chung
gro.griffith.authorZhao, Huijun


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