title: 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.
authors.affiliation: I.R.I.B.H.N., Campus Hopital Erasme, Route de Lennik 808 Bat C-CP602, Brussels, B-1070, Belgium. davenet@ulb.ac.be
authors.forename: D
authors.initials: D
authors.lastname: Venet
authors.forename: F
authors.initials: F
authors.lastname: Pecasse
authors.forename: C
authors.initials: C
authors.lastname: Maenhaut
authors.forename: H
authors.initials: H
authors.lastname: Bersini
mesh_terms: 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
chemical_list: D012333:RNA, Messenger