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BIOINFORMATICS
2007
195views more  BIOINFORMATICS 2007»
14 years 9 months ago
Context-dependent clustering for dynamic cellular state modeling of microarray gene expression
Motivation: High-throughput expression profiling allows researchers to study gene activities globally. Genes with similar expression profiles are likely to encode proteins that ma...
Shinsheng Yuan, Ker-Chau Li
BMCBI
2010
124views more  BMCBI 2010»
14 years 9 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...
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BMCBI
2002
188views more  BMCBI 2002»
14 years 9 months ago
The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data
Background: The biomedical community is developing new methods of data analysis to more efficiently process the massive data sets produced by microarray experiments. Systematic an...
David M. Mutch, Alvin Berger, Robert Mansourian, A...
JMLR
2008
94views more  JMLR 2008»
14 years 9 months ago
Using Markov Blankets for Causal Structure Learning
We show how a generic feature selection algorithm returning strongly relevant variables can be turned into a causal structure learning algorithm. We prove this under the Faithfuln...
Jean-Philippe Pellet, André Elisseeff
BMCBI
2006
167views more  BMCBI 2006»
14 years 9 months ago
GOurmet: A tool for quantitative comparison and visualization of gene expression profiles based on gene ontology (GO) distributi
Background: The ever-expanding population of gene expression profiles (EPs) from specified cells and tissues under a variety of experimental conditions is an important but difficu...
Jason M. Doherty, Lynn K. Carmichael, Jason C. Mil...