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Clustering cancer gene expression data: a comparative study |
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| Authors: | Marcilio CP de Souto Ivan G Costa Daniel SA de Araujo Teresa B Ludermir Alexander Schliep |
| Institution: | (1) Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany;(2) Dept. of Informatics and Applied Mathematics, Fed. Univ. of Rio Grande do Norte, Natal, Brazil;(3) Center of Informatics, Federal University of Pernambuco, Recife, Brazil |
| Abstract: | BackgroundThe 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. |
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