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BMCBI
2006
153views more  BMCBI 2006»
13 years 4 months ago
Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments
Background: The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating v...
Maureen A. Sartor, Craig R. Tomlinson, Scott C. We...
BMCBI
2007
114views more  BMCBI 2007»
13 years 4 months ago
Large scale statistical inference of signaling pathways from RNAi and microarray data
Background: The advent of RNA interference techniques enables the selective silencing of biologically interesting genes in an efficient way. In combination with DNA microarray tec...
Holger Fröhlich, Mark Fellmann, Holger Sü...
BIB
2007
59views more  BIB 2007»
13 years 4 months ago
Statistically designing microarrays and microarray experiments to enhance sensitivity and specificity
Gene expression signatures from microarray experiments promise to provide important prognostic tools for predicting disease outcome or response to treatment. A number of microarra...
Jason C. Hsu, Jane Chang, Tao Wang, Eiríkur...
BMCBI
2007
130views more  BMCBI 2007»
13 years 4 months ago
Reproducibility of microarray data: a further analysis of microarray quality control (MAQC) data
Background: Many researchers are concerned with the comparability and reliability of microarray gene expression data. Recent completion of the MicroArray Quality Control (MAQC) pr...
James J. Chen, Huey-miin Hsueh, Robert R. Delongch...
BMCBI
2008
159views more  BMCBI 2008»
13 years 4 months ago
Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
Hongya Zhao, Kwok-Leung Chan, Lee-Ming Cheng, Hong...