An integrated approach of particle swarm optimization and support vector machine for gene signature selection and cancer prediction

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An integrated approach of particle swarm optimization and support vector machine for gene signature selection and cancer prediction

To improve cancer diagnosis and drug development, the classification of tumor types based on genomic information is important. As DNA micro array studies produce a large amount of data, expression data are highly redundant and noisy, and most genes are believed to be uninformative with respect to th...

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Bibliographic Details
Main Authors:	Yeung, C., Chan, Kit Yan
Other Authors:	Robert Kozma
Format:	Conference Paper
Published:	IEEE Press 2009
Online Access:	http://portal.acm.org/citation.cfm?id=1704425 http://hdl.handle.net/20.500.11937/40087

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