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dc.contributor.authorLiew, Alan Wee-Chung
dc.contributor.authorLaw, Ngai-Fong
dc.contributor.authorYan, Hong
dc.contributor.editorJ.R.R. Dopico, J. Dorado, A. Pazos
dc.date.accessioned2018-01-11T03:18:13Z
dc.date.available2018-01-11T03:18:13Z
dc.date.issued2009
dc.date.modified2014-02-07T06:03:30Z
dc.identifier.isbn9781599048499en_US
dc.identifier.doi10.4018/978-1-59904-849-9.ch045en_US
dc.identifier.urihttp://hdl.handle.net/10072/26559
dc.description.abstractImportant insights into gene function can be gained by gene expression analysis. For example, some genes are turned on (expressed) or turned off (repressed) when there is a change in external conditions or stimuli. The expression of one gene is often regulated by the expression of other genes. A detail analysis of gene expression information will provide an understanding about the inter-networking of different genes and their functional roles. DNA microarray technology allows massively parallel, high throughput genome-wide profiling of gene expression in a single hybridization experiment [Lockhart & Winzeler, 2000]. It has been widely used in numerous studies over a broad range of biological disciplines, such as cancer classification (Armstrong et al., 2002), identification of genes relevant to a certain diagnosis or therapy (Muro et al., 2003), investigation of the mechanism of drug action and cancer prognosis (Kim et al., 2000; Duggan et al., 1999). Due to the large number of genes involved in microarray experiment study and the complexity of biological networks, clustering is an important exploratory technique for gene expression data analysis. In this article, we present a succinct review of some of our work in cluster analysis of gene expression data.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.languageEnglishen_US
dc.language.isoen_US
dc.publisherInformation Science Reference, IGI Global Publishingen_US
dc.publisher.placeUnited Statesen_US
dc.publisher.urihttp://dx.doi.org/10.4018/978-1-59904-849-9en_US
dc.relation.ispartofbooktitleEncyclopedia of Artificial Intelligenceen_US
dc.relation.ispartofchapter45en_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofpagefrom289en_US
dc.relation.ispartofpageto296en_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchPattern Recognition and Data Miningen_US
dc.subject.fieldofresearchcode080109en_US
dc.titleCluster Analysis of Gene Expression Dataen_US
dc.typeBook chapteren_US
dc.type.descriptionB1 - Book Chapters (HERDC)en_US
dc.type.codeB - Book Chaptersen_US
gro.facultyGriffith Sciences, School of Information and Communication Technologyen_US
gro.date.issued2009
gro.hasfulltextNo Full Text


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