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» Combined Gene Selection Methods for Microarray Data Analysis
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143
Voted
BMCBI
2010
153views more  BMCBI 2010»
15 years 1 months ago
DiffCoEx: a simple and sensitive method to find differentially coexpressed gene modules
Background: Large microarray datasets have enabled gene regulation to be studied through coexpression analysis. While numerous methods have been developed for identifying differen...
Bruno M. Tesson, Rainer Breitling, Ritsert C. Jans...
BIBM
2008
IEEE
212views Bioinformatics» more  BIBM 2008»
15 years 9 months ago
Analysis of Multiplex Gene Expression Maps Obtained by Voxelation
Background: Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelatio...
Li An, Hongbo Xie, Mark H. Chin, Zoran Obradovic, ...
128
Voted
BMCBI
2006
115views more  BMCBI 2006»
15 years 2 months ago
Multivariate curve resolution of time course microarray data
Background: Modeling of gene expression data from time course experiments often involves the use of linear models such as those obtained from principal component analysis (PCA), i...
Peter D. Wentzell, Tobias K. Karakach, Sushmita Ro...
BMCBI
2007
105views more  BMCBI 2007»
15 years 2 months ago
Extended analysis of benchmark datasets for Agilent two-color microarrays
Background: As part of its broad and ambitious mission, the MicroArray Quality Control (MAQC) project reported the results of experiments using External RNA Controls (ERCs) on fiv...
Kathleen F. Kerr
143
Voted
BMCBI
2005
151views more  BMCBI 2005»
15 years 2 months ago
stam - a Bioconductor compliant R package for structured analysis of microarray data
Background: Genome wide microarray studies have the potential to unveil novel disease entities. Clinically homogeneous groups of patients can have diverse gene expression profiles...
Claudio Lottaz, Rainer Spang