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» The statistics of identifying differentially expressed genes...
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BMCBI
2005
113views more  BMCBI 2005»
13 years 4 months ago
Pathway level analysis of gene expression using singular value decomposition
Background: A promising direction in the analysis of gene expression focuses on the changes in expression of specific predefined sets of genes that are known in advance to be rela...
John K. Tomfohr, Jun Lu, Thomas B. Kepler
BMCBI
2008
126views more  BMCBI 2008»
13 years 5 months ago
Relating gene expression data on two-component systems to functional annotations in Escherichia coli
Background: Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionall...
Anne M. Denton, Jianfei Wu, Megan K. Townsend, Pre...
CGF
2008
142views more  CGF 2008»
13 years 5 months ago
Visualizing Genome Expression and Regulatory Network Dynamics in Genomic and Metabolic Context
DNA microarrays are used to measure the expression levels of thousands of genes simultaneously. In a time series experiment, the gene expressions are measured as a function of tim...
Michel A. Westenberg, Sacha A. F. T. van Hijum, Os...
BMCBI
2007
125views more  BMCBI 2007»
13 years 5 months ago
Bayesian meta-analysis models for microarray data: a comparative study
Background: With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis...
Erin M. Conlon, Joon J. Song, Anna Liu
BMCBI
2005
163views more  BMCBI 2005»
13 years 4 months ago
Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data
Background: The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in microarray studies. Classical p-value adjustm...
Nitin Jain, HyungJun Cho, Michael O'Connell, Jae K...