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» CoXpress: differential co-expression in gene expression data
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BMCBI
2006
86views more  BMCBI 2006»
13 years 8 months ago
The impact of sample imbalance on identifying differentially expressed genes
Background: Recently several statistical methods have been proposed to identify genes with differential expression between two conditions. However, very few studies consider the p...
Kun Yang, Jianzhong Li, Hong Gao
BMCBI
2008
97views more  BMCBI 2008»
13 years 8 months ago
A Population Proportion approach for ranking differentially expressed genes
Background: DNA microarrays are used to investigate differences in gene expression between two or more classes of samples. Most currently used approaches compare mean expression l...
Mugdha Gadgil
BMCBI
2006
126views more  BMCBI 2006»
13 years 8 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
2007
173views more  BMCBI 2007»
13 years 8 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
BMCBI
2006
131views more  BMCBI 2006»
13 years 8 months ago
The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison
Background: Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, t...
Allan A. Sioson, Shrinivasrao P. Mane, Pinghua Li,...