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» Semantic Mining and Analysis of Gene Expression Data
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BMCBI
2004
146views more  BMCBI 2004»
13 years 8 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
2002
188views more  BMCBI 2002»
13 years 8 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...
BMCBI
2010
124views more  BMCBI 2010»
13 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...
BIOINFORMATICS
2005
151views more  BIOINFORMATICS 2005»
13 years 8 months ago
Differential and trajectory methods for time course gene expression data
Motivation: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differen...
Yulan Liang, Bamidele Tayo, Xueya Cai, Arpad Kelem...
BMCBI
2007
130views more  BMCBI 2007»
13 years 9 months ago
A model-based optimization framework for the inference of regulatory interactions using time-course DNA microarray expression da
Background: Proteins are the primary regulatory agents of transcription even though mRNA expression data alone, from systems like DNA microarrays, are widely used. In addition, th...
Reuben Thomas, Carlos J. Paredes, Sanjay Mehrotra,...