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BMCBI
2008
160views more  BMCBI 2008»
13 years 4 months ago
A method for analyzing censored survival phenotype with gene expression data
Background: Survival time is an important clinical trait for many disease studies. Previous works have shown certain relationship between patients' gene expression profiles a...
Tongtong Wu, Wei Sun, Shinsheng Yuan, Chun-Houh Ch...
BMCBI
2007
182views more  BMCBI 2007»
13 years 4 months ago
Additive risk survival model with microarray data
Background: Microarray techniques survey gene expressions on a global scale. Extensive biomedical studies have been designed to discover subsets of genes that are associated with ...
Shuangge Ma, Jian Huang
ISMB
2000
13 years 5 months ago
Analysis of Gene Expression Microarrays for Phenotype Classification
Several microarray technologies that monitor the level of expression of a large number of genes have recently emerged. Given DNA-microarray data for a set of cells characterized b...
Andrea Califano, Gustavo Stolovitzky, Yuhai Tu
BMCBI
2010
124views more  BMCBI 2010»
13 years 4 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...
BMCBI
2010
85views more  BMCBI 2010»
13 years 4 months ago
Robust test method for time-course microarray experiments
Background: In a time-course microarray experiment, the expression level for each gene is observed across a number of time-points in order to characterize the temporal trajectorie...
Insuk Sohn, Kouros Owzar, Stephen L. George, Sujon...