Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/114981
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dc.titleA new method on gene selection for tissue classification
dc.contributor.authorHao, Y.
dc.contributor.authorMeng, F.
dc.date.accessioned2014-12-12T07:09:32Z
dc.date.available2014-12-12T07:09:32Z
dc.date.issued2007
dc.identifier.citationHao, Y.,Meng, F. (2007). A new method on gene selection for tissue classification. Journal of Industrial and Management Optimization 3 (4) : 739-748. ScholarBank@NUS Repository.
dc.identifier.issn15475816
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/114981
dc.description.abstractTumor classification is one of the important applications of microarray technology. In gene expression-based tumor classification systems, gene selection is a main and very important component. In this paper, we propose a new approach for gene selection. With the genes selected in colon cancer data, acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) data using our approach, we apply support vector machines to classify tissues in these two data sets, respectively. The results of classification show that our method is very useful and promising.
dc.sourceScopus
dc.subjectClassification
dc.subjectFisher's linear discriminant
dc.subjectGene selection
dc.subjectSupport vector machines
dc.typeArticle
dc.contributor.departmentTHE LOGISTICS INSTITUTE - ASIA PACIFIC
dc.description.sourcetitleJournal of Industrial and Management Optimization
dc.description.volume3
dc.description.issue4
dc.description.page739-748
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Staff Publications

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