Separation of samples into their constituents using gene expression data

Abstract

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. Contact: davenet@ulb.ac.be

Keywords

Gene expressionComputational biologyExpression (computer science)Set (abstract data type)GeneData setSample (material)BiologyGene expression profilingComputer scienceGeneticsArtificial intelligenceChromatographyChemistry

Affiliated Institutions

Erasmus Hospital BE

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Publication Info

Year: 2001
Type: article
Volume: 17
Issue: suppl_1
Pages: S279-S287
Citations: 145
Access: Closed

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APA Style

                            
                                
                                    David Venet, 
                                
                                    Frédéric Pecasse, 
                                
                                    Carine Maenhaut
                                
                                et al.
                            
                            (2001). 
                            Separation of samples into their constituents using gene expression data. 
                            Bioinformatics
                            , 17
                            (suppl_1)
                            , S279-S287.
                            https://doi.org/10.1093/bioinformatics/17.suppl_1.s279
                        

Identifiers

DOI: 10.1093/bioinformatics/17.suppl_1.s279