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BMCBI
2007
171views more  BMCBI 2007»
13 years 7 months ago
Classification of microarray data using gene networks
Background: Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) a...
Franck Rapaport, Andrei Zinovyev, Marie Dutreix, E...
BMCBI
2004
106views more  BMCBI 2004»
13 years 7 months ago
Spotting effect in microarray experiments
Background: Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects...
Tristan Mary-Huard, Jean-Jacques Daudin, Sté...
BMCBI
2006
130views more  BMCBI 2006»
13 years 7 months ago
CARMA: A platform for analyzing microarray datasets that incorporate replicate measures
Background: The incorporation of statistical models that account for experimental variability provides a necessary framework for the interpretation of microarray data. A robust ex...
Kevin A. Greer, Matthew R. McReynolds, Heddwen L. ...
BMCBI
2007
163views more  BMCBI 2007»
13 years 7 months ago
Use of genomic DNA control features and predicted operon structure in microarray data analysis: ArrayLeaRNA - a Bayesian approac
Background: Microarrays are widely used for the study of gene expression; however deciding on whether observed differences in expression are significant remains a challenge. Resul...
Carmen Pin, Mark Reuter
BMCBI
2005
169views more  BMCBI 2005»
13 years 7 months ago
An adaptive method for cDNA microarray normalization
Background: Normalization is a critical step in analysis of gene expression profiles. For duallabeled arrays, global normalization assumes that the majority of the genes on the ar...
Yingdong Zhao, Ming-Chung Li, Richard Simon