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» Analysis of variance components in gene expression data
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BMCBI
2010
165views more  BMCBI 2010»
14 years 10 months ago
Filtering, FDR and power
Background: In high-dimensional data analysis such as differential gene expression analysis, people often use filtering methods like fold-change or variance filters in an attempt ...
Maarten van Iterson, Judith M. Boer, Renée ...
BMCBI
2006
126views more  BMCBI 2006»
14 years 10 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
148views more  BMCBI 2005»
14 years 9 months ago
Nonparametric tests for differential gene expression and interaction effects in multi-factorial microarray experiments
Background: Numerous nonparametric approaches have been proposed in literature to detect differential gene expression in the setting of two user-defined groups. However, there is ...
Xin Gao, Peter X. K. Song
BMCBI
2004
131views more  BMCBI 2004»
14 years 9 months ago
Alternative mapping of probes to genes for Affymetrix chips
Background: Short oligonucleotide arrays have several probes measuring the expression level of each target transcript. Therefore the selection of probes is a key component for the...
Laurent Gautier, Morten Møller, Lennart Fri...
KDD
2003
ACM
133views Data Mining» more  KDD 2003»
15 years 10 months ago
Interactive Analysis of Gene Interactions Using Graphical gaussian model
DNA microarray provides a powerful basis for analysis of gene expression. Data mining methods such as clustering have been widely applied to microarray data to link genes that sho...
Xintao Wu, Yong Ye, Kalpathi R. Subramanian