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BMCBI
2008
159views more  BMCBI 2008»
13 years 8 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...
APBC
2004
107views Bioinformatics» more  APBC 2004»
13 years 9 months ago
An Empirical Bayes Adjustment to Multiple p-values for the Detection of Differentially Expressed Genes in Microarray Experiments
In recent microarray experiments thousands of gene expressions are simultaneously tested in comparing samples (e.g., tissue types or experimental conditions). Application of a sta...
Somnath Datta, Susmita Datta
BMCBI
2006
112views more  BMCBI 2006»
13 years 8 months ago
Assessment of the relationship between pre-chip and post-chip quality measures for Affymetrix GeneChip expression data
Background: Gene expression microarray experiments are expensive to conduct and guidelines for acceptable quality control at intermediate steps before and after the samples are hy...
Lesley Jones, Darlene R. Goldstein, Gareth P. Hugh...
BMCBI
2008
99views more  BMCBI 2008»
13 years 8 months ago
Ranking analysis of F-statistics for microarray data
Background: Microarray technology provides an efficient means for globally exploring physiological processes governed by the coordinated expression of multiple genes. However, ide...
Yuan-De Tan, Myriam Fornage, Hongyan Xu
BMCBI
2006
153views more  BMCBI 2006»
13 years 8 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...