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BMCBI
2004
146views more  BMCBI 2004»
13 years 7 months ago
Multivariate search for differentially expressed gene combinations
Background: To identify differentially expressed genes, it is standard practice to test a twosample hypothesis for each gene with a proper adjustment for multiple testing. Such te...
Yuanhui Xiao, Robert D. Frisina, Alexander Gordon,...
BMCBI
2006
171views more  BMCBI 2006»
13 years 7 months ago
The effect of oligonucleotide microarray data pre-processing on the analysis of patient-cohort studies
Background: Intensity values measured by Affymetrix microarrays have to be both normalized, to be able to compare different microarrays by removing non-biological variation, and s...
Roel G. W. Verhaak, Frank J. T. Staal, Peter J. M....
BMCBI
2008
126views more  BMCBI 2008»
13 years 7 months ago
Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution
Background: In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. Howe...
Stefano Moretti, Danitsja van Leeuwen, Hans Gmuend...
BMCBI
2004
135views more  BMCBI 2004»
13 years 7 months ago
Determination of the differentially expressed genes in microarray experiments using local FDR
Background: Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expect...
Julie Aubert, Avner Bar-Hen, Jean-Jacques Daudin, ...
BMCBI
2008
138views more  BMCBI 2008»
13 years 7 months ago
M-BISON: Microarray-based integration of data sources using networks
Background: The accurate detection of differentially expressed (DE) genes has become a central task in microarray analysis. Unfortunately, the noise level and experimental variabi...
Bernie J. Daigle Jr., Russ B. Altman