Separation of samples into their constituents using gene expression data.
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.
Venet
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I.R.I.B.H.N., Campus Hopital Erasme, Route de Lennik 808 Bat C-CP602, Brussels, B-1070, Belgium. davenet@ulb.ac.be
Pecasse
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Maenhaut
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Bersini
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D000465:Algorithms; D002477:Cells / Q000378:metabolism; D003110:Colonic Neoplasms / Q000235:genetics; D019295:Computational Biology; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000706:statistics & numerical data*; D006801:Humans; D008957:Models, Genetic; D025341:Principal Component Analysis; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism
D012333:RNA, Messenger