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» Analysis of Variance for Gene Expression Microarray Data
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BMCBI
2008
121views more  BMCBI 2008»
15 years 1 months ago
Stability of gene contributions and identification of outliers in multivariate analysis of microarray data
Background: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages com...
Florent Baty, Daniel Jaeger, Frank Preiswerk, Mart...
BMCBI
2010
123views more  BMCBI 2010»
15 years 1 months ago
Prediction of breast cancer prognosis using gene set statistics provides signature stability and biological context
Background: Different microarray studies have compiled gene lists for predicting outcomes of a range of treatments and diseases. These have produced gene lists that have little ov...
Gad Abraham, Adam Kowalczyk, Sherene Loi, Izhak Ha...
BMCBI
2008
135views more  BMCBI 2008»
15 years 1 months ago
Knowledge-guided multi-scale independent component analysis for biomarker identification
Background: Many statistical methods have been proposed to identify disease biomarkers from gene expression profiles. However, from gene expression profile data alone, statistical...
Li Chen, Jianhua Xuan, Chen Wang, Ie-Ming Shih, Yu...
BMCBI
2004
146views more  BMCBI 2004»
15 years 1 months ago
Multivariate search for differentially expressed gene combinations
Background: To identify differentially expressed genes, it is standard practice to test a twosample hypothesis for each gene with a proper adjustment for multiple testing. Such te...
Yuanhui Xiao, Robert D. Frisina, Alexander Gordon,...
BMCBI
2010
124views more  BMCBI 2010»
15 years 1 months ago
A factor model to analyze heterogeneity in gene expression
Background: Microarray technology allows the simultaneous analysis of thousands of genes within a single experiment. Significance analyses of transcriptomic data ignore the gene d...
Yuna Blum, Guillaume Le Mignon, Sandrine Lagarrigu...