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Blind Matrix Decomposition Techniques to Identify Marker Genes from Microarrays

Authors :
Dominik Lutter
Ana Maria Tomé
Fabian J. Theis
J. M. Gorriz Saez
Elmar Lang
R. Schachtner
Carlos G. Puntonet
Source :
Independent Component Analysis and Signal Separation ISBN: 9783540744931, ICA
Publication Year :
2007
Publisher :
Springer Berlin Heidelberg, 2007.

Abstract

Exploratory matrix factorization methods like PCA, ICA and sparseNMF are applied to identify marker genes and classify gene expression data sets into different categories for diagnostic purposes or group genes into functional categories for further investigation of related regulatory pathways. Gene expression levels of either human breast cancer (HBC) cell lines [6] or the famous leucemia data set [10] are considered.

Details

ISBN :
978-3-540-74493-1
ISBNs :
9783540744931
Database :
OpenAIRE
Journal :
Independent Component Analysis and Signal Separation ISBN: 9783540744931, ICA
Accession number :
edsair.doi...........8b55c474e1e1747c66d434c7c3e2516f
Full Text :
https://doi.org/10.1007/978-3-540-74494-8_81