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CSDA
2007
151views more  CSDA 2007»
13 years 7 months ago
Robust semiparametric mixing for detecting differentially expressed genes in microarray experiments
An important goal of microarray studies is the detection of genes that show significant changes in observed expressions when two or more classes of biological samples such as tre...
Marco Alfò, Alessio Farcomeni, Luca Tardell...
BMCBI
2005
212views more  BMCBI 2005»
13 years 7 months ago
PAGE: Parametric Analysis of Gene Set Enrichment
Background: Gene set enrichment analysis (GSEA) is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes i...
Seon-Young Kim, David J. Volsky
ITSSA
2006
109views more  ITSSA 2006»
13 years 7 months ago
Gene Expression Analysis in Multi-Agent Environment
Abstract. This paper presents a multi-agent approach to gene expression analysis and illustrates the working steps using real dataset produced from a microarray experiment. The ana...
H. C. Lam, M. Vazquez, B. Juneja, Scott C. Fahrenk...
RECOMB
2006
Springer
14 years 8 months ago
A Patient-Gene Model for Temporal Expression Profiles in Clinical Studies
Abstract. Pharmacogenomics and clinical studies that measure the temporal expression levels of patients can identify important pathways and biomarkers that are activated during dis...
Naftali Kaminski, Ziv Bar-Joseph
BMCBI
2008
98views more  BMCBI 2008»
13 years 7 months ago
GBNet: Deciphering regulatory rules in the co-regulated genes using a Gibbs sampler enhanced Bayesian network approach
Background: Combinatorial regulation of transcription factors (TFs) is important in determining the complex gene expression patterns particularly in higher organisms. Deciphering ...
Li Shen, Jie Liu, Wei Wang