Robust diagnosis of non-Hodgkin lymphoma phenotypes validated on gene expression data from different laboratories.

Abstract excerpt

A major challenge in cancer diagnosis from microarray data is the need for robust, accurate, classification models which are independent of the analysis techniques used and can combine data from different laboratories. We propose such a classification scheme originally developed for phenotype identification from mass spectrometry data. The method uses a robust multivariate gene selection procedure and combines...

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