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Cancer characterization and feature set extraction by discriminative margin clustering
2004
BMC Bioinformatics
A central challenge in the molecular diagnosis and treatment of cancer is to define a set of molecular features that, taken together, distinguish a given cancer, or type of cancer, from all normal cells and tissues. Discriminative margin clustering is a new technique for analyzing high dimensional quantitative datasets, specially applicable to gene expression data from microarray experiments related to cancer. The goal of the analysis is find highly specialized sub-types of a tumor type which
doi:10.1186/1471-2105-5-21
pmid:15070405
pmcid:PMC385290
fatcat:w7dcc3dzcjgbfd6kcz72pkhqpu