Exploiting scale-free information from expression data for cancer classification
Alexey V. Antonov
, Igor V. Tetko
, Denis Kosykh
, Dmitrij Surmeli
and Hans-Wernermewes
Abstract
In most studies concerning expression data analyses information on the variability of gene intensity across samples is usually exploited. This information is sensitive to initial data processing which affects the final conclusions. However expression data contains scale free information which is directly comparable between different samples. We propose to use the pairwise ratio of gene expression
Full Text: PDF