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» Mixture Models for Detecting Differentially Expressed Genes ...
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BMCBI
2007
135views more  BMCBI 2007»
13 years 7 months ago
Detecting multivariate differentially expressed genes
Background: Gene expression is governed by complex networks, and differences in expression patterns between distinct biological conditions may therefore be complex and multivariat...
Roland Nilsson, José M. Peña, Johan ...
BIOINFORMATICS
2005
151views more  BIOINFORMATICS 2005»
13 years 7 months ago
Differential and trajectory methods for time course gene expression data
Motivation: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differen...
Yulan Liang, Bamidele Tayo, Xueya Cai, Arpad Kelem...
BIOINFORMATICS
2005
72views more  BIOINFORMATICS 2005»
13 years 7 months ago
Use of within-array replicate spots for assessing differential expression in microarray experiments
Motivation. Spotted arrays are often printed with probes in duplicate or triplicate, but current methods for assessing differential expression are not able to make full use of the...
Gordon K. Smyth, Joëlle Michaud, Hamish S. Sc...
BMCBI
2010
96views more  BMCBI 2010»
13 years 7 months ago
A statistical framework for differential network analysis from microarray data
Background: It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of gene...
Ryan Gill, Somnath Datta, Susmita Datta
BMCBI
2007
149views more  BMCBI 2007»
13 years 7 months ago
Novel and simple transformation algorithm for combining microarray data sets
Background: With microarray technology, variability in experimental environments such as RNA sources, microarray production, or the use of different platforms, can cause bias. Suc...
Ki-Yeol Kim, Dong Hyuk Ki, Ha Jin Jeong, Hei-Cheul...