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Article: On mining micro-array data by order-preserving submatrix

TitleOn mining micro-array data by order-preserving submatrix
Authors
Issue Date2007
PublisherInderscience Publishers. The Journal's web site is located at http://www.inderscience.com/ijbra
Citation
International Journal Of Bioinformatics Research And Applications, 2007, v. 3 n. 1, p. 42-64 How to Cite?
AbstractWe study the problem of pattern-based subspace clustering which is clustering by pattern similarity finds objects that exhibit a coherent pattern of rises and falls in subspaces. Applications of pattern-based subspace clustering include DNA micro-array data analysis. Our goal is to devise pattern-based clustering methods that are capable of • discovering useful patterns of various shapes • discovering all significant patterns. Our approach is to extend the idea of Order-Preserving Submatrix (OPSM). We devise a novel algorithm for mining OPSM, show that OPSM can be generalised to cover most existing pattern-based clustering models and propose a number of extensions to the original OPSM model. Copyright © 2007 Inderscience Enterprises Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/89059
ISSN
2015 SCImago Journal Rankings: 0.231
References

 

DC FieldValueLanguage
dc.contributor.authorCheung, Len_HK
dc.contributor.authorCheung, DWen_HK
dc.contributor.authorKao, Ben_HK
dc.contributor.authorYip, KYen_HK
dc.contributor.authorNg, MKen_HK
dc.date.accessioned2010-09-06T09:51:52Z-
dc.date.available2010-09-06T09:51:52Z-
dc.date.issued2007en_HK
dc.identifier.citationInternational Journal Of Bioinformatics Research And Applications, 2007, v. 3 n. 1, p. 42-64en_HK
dc.identifier.issn1744-5485en_HK
dc.identifier.urihttp://hdl.handle.net/10722/89059-
dc.description.abstractWe study the problem of pattern-based subspace clustering which is clustering by pattern similarity finds objects that exhibit a coherent pattern of rises and falls in subspaces. Applications of pattern-based subspace clustering include DNA micro-array data analysis. Our goal is to devise pattern-based clustering methods that are capable of • discovering useful patterns of various shapes • discovering all significant patterns. Our approach is to extend the idea of Order-Preserving Submatrix (OPSM). We devise a novel algorithm for mining OPSM, show that OPSM can be generalised to cover most existing pattern-based clustering models and propose a number of extensions to the original OPSM model. Copyright © 2007 Inderscience Enterprises Ltd.en_HK
dc.languageengen_HK
dc.publisherInderscience Publishers. The Journal's web site is located at http://www.inderscience.com/ijbraen_HK
dc.relation.ispartofInternational Journal of Bioinformatics Research and Applicationsen_HK
dc.subject.meshAlgorithmsen_HK
dc.subject.meshArtificial Intelligenceen_HK
dc.subject.meshCluster Analysisen_HK
dc.subject.meshComputational Biology - methodsen_HK
dc.subject.meshDNA - chemistryen_HK
dc.subject.meshData Interpretation, Statisticalen_HK
dc.subject.meshGene Expression Profiling - methodsen_HK
dc.subject.meshGene Expression Regulationen_HK
dc.subject.meshImage Interpretation, Computer-Assisteden_HK
dc.subject.meshInformation Storage and Retrievalen_HK
dc.subject.meshModels, Geneticen_HK
dc.subject.meshModels, Statisticalen_HK
dc.subject.meshOligonucleotide Array Sequence Analysis - methodsen_HK
dc.subject.meshPattern Recognition, Automateden_HK
dc.titleOn mining micro-array data by order-preserving submatrixen_HK
dc.typeArticleen_HK
dc.identifier.emailCheung, DW:dcheung@cs.hku.hken_HK
dc.identifier.emailKao, B:kao@cs.hku.hken_HK
dc.identifier.authorityCheung, DW=rp00101en_HK
dc.identifier.authorityKao, B=rp00123en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1504/IJBRA.2007.011834en_HK
dc.identifier.pmid18048172-
dc.identifier.scopuseid_2-s2.0-33947492312en_HK
dc.identifier.hkuros129361en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33947492312&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume3en_HK
dc.identifier.issue1en_HK
dc.identifier.spage42en_HK
dc.identifier.epage64en_HK
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridCheung, L=36840358100en_HK
dc.identifier.scopusauthoridCheung, DW=34567902600en_HK
dc.identifier.scopusauthoridKao, B=35221592600en_HK
dc.identifier.scopusauthoridYip, KY=7101909946en_HK
dc.identifier.scopusauthoridNg, MK=34571761900en_HK

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