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BMCBI
2004

Cancer characterization and feature set extraction by discriminative margin clustering

8 years 12 months ago
Cancer characterization and feature set extraction by discriminative margin clustering
Background: 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. Results: 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 are similar in having a small combination of genes which together provide a unique molecular portrait for distinguishing the sub-type from any normal cell or tissue. Detection of the products of these genes can then, in principle, provide a basis for detection and diagnosis of a cancer, and a therapy directed specifically at the distinguishing constellation of molecular features can, in principle, provide a way to eliminate the cancer cells, while minimizing toxicity to any n...
Kamesh Munagala, Robert Tibshirani, Patrick O. Bro
Added 16 Dec 2010
Updated 16 Dec 2010
Type Journal
Year 2004
Where BMCBI
Authors Kamesh Munagala, Robert Tibshirani, Patrick O. Brown
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