Clustering cancer gene expression data: a comparative study
Open Access
- 27 November 2008
- journal article
- Published by Springer Nature in BMC Bioinformatics
- Vol. 9 (1) , 497
Abstract
The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have proposed new clustering methods that take advantage of characteristics of the gene expression data, the medical community has a preference for using "classic" clustering methods. There have been no studies thus far performing a large-scale evaluation of different clustering methods in this context.Keywords
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