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...
| Main Authors: | , |
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| Format: | Conference Paper |
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IEEE Press
2009
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| Online Access: | http://portal.acm.org/citation.cfm?id=1704425 http://hdl.handle.net/20.500.11937/40087 |