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BMCBI
2006
126views more  BMCBI 2006»
13 years 7 months ago
OpWise: Operons aid the identification of differentially expressed genes in bacterial microarray experiments
Background: Differentially expressed genes are typically identified by analyzing the variation between replicate measurements. These procedures implicitly assume that there are no...
Morgan N. Price, Adam P. Arkin, Eric J. Alm
BMCBI
2005
126views more  BMCBI 2005»
13 years 7 months ago
Integrative analysis of multiple gene expression profiles with quality-adjusted effect size models
Background: With the explosion of microarray studies, an enormous amount of data is being produced. Systematic integration of gene expression data from different sources increases...
Pingzhao Hu, Celia M. T. Greenwood, Joseph Beyene
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
2004
154views more  BMCBI 2004»
13 years 7 months ago
Accuracy of cDNA microarray methods to detect small gene expression changes induced by neuregulin on breast epithelial cells
Background: cDNA microarrays are a powerful means to screen for biologically relevant gene expression changes, but are often limited by their ability to detect small changes accur...
Bin Yao, Sanjay N. Rakhade, Qunfang Li, Sharlin Ah...
BMCBI
2011
12 years 11 months ago
A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression
Background: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) ...
Alfredo A. Kalaitzis, Neil D. Lawrence