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» Microarray Gene Expression Data Analysis
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BMCBI
2008
98views more  BMCBI 2008»
15 years 2 months ago
Empirical Bayes models for multiple probe type microarrays at the probe level
Background: When analyzing microarray data a primary objective is often to find differentially expressed genes. With empirical Bayes and penalized t-tests the sample variances are...
Magnus Åstrand, Petter Mostad, Mats Rudemo
BMCBI
2010
104views more  BMCBI 2010»
15 years 2 months ago
Response network analysis of differential gene expression in human epithelial lung cells during avian influenza infections
Background: The recent emergence of the H5N1 influenza virus from avian reservoirs has raised concern about future influenza strains of high virulence emerging that could easily i...
Ken Tatebe, Ahmet Zeytun, Ruy M. Ribeiro, Robert H...
123
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DSS
2007
127views more  DSS 2007»
15 years 2 months ago
Large-scale regulatory network analysis from microarray data: modified Bayesian network learning and association rule mining
We present two algorithms for learning large-scale gene regulatory networks from microarray data: a modified informationtheory-based Bayesian network algorithm and a modified asso...
Zan Huang, Jiexun Li, Hua Su, George S. Watts, Hsi...
150
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ICMLA
2010
15 years 15 days ago
Smoothing Gene Expression Using Biological Networks
Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
Yue Fan, Mark A. Kon, Shinuk Kim, Charles DeLisi
127
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BMCBI
2008
154views more  BMCBI 2008»
15 years 2 months ago
Bayesian models and meta analysis for multiple tissue gene expression data following corticosteroid administration
Background: This paper addresses key biological problems and statistical issues in the analysis of large gene expression data sets that describe systemic temporal response cascade...
Yulan Liang, Arpad Kelemen