Separation of samples into their constituents using gene expression data

Abstract

Gene expression measurements are a powerful tool in molecular biology, but when applied to heterogeneous samples containing more than one cellular type the results are difficult to interpret. We present here a new approach to this problem allowing to deduce the gene expression profile of the various cellular types contained in a set of samples directly from the measurements taken on the whole sample.

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@article{Venet2001SeparationOS, title={Separation of samples into their constituents using gene expression data}, author={David Venet and F. Pecasse and C. Maenhaut and Hugues Bersini}, journal={Bioinformatics}, year={2001}, volume={17 Suppl 1}, pages={S279-87} }