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» CoXpress: differential co-expression in gene expression data
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BMCBI
2008
126views more  BMCBI 2008»
13 years 7 months ago
Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution
Background: In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. Howe...
Stefano Moretti, Danitsja van Leeuwen, Hans Gmuend...
BMCBI
2004
146views more  BMCBI 2004»
13 years 7 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
2004
124views more  BMCBI 2004»
13 years 7 months ago
Tests for finding complex patterns of differential expression in cancers: towards individualized medicine
Background: Microarray studies in cancer compare expression levels between two or more sample groups on thousands of genes. Data analysis follows a population-level approach (e.g....
James Lyons-Weiler, Satish Patel, Michael J. Becic...
BMEI
2009
IEEE
13 years 8 months ago
An Improved Probabilistic Model for Finding Differential Gene Expression
Abstract--Finding differentially expressed genes is a fundamental objective of a microarray experiment. Recently proposed method, PPLR, considers the probe-level measurement error ...
Li Zhang, Xuejun Liu
BMCBI
2008
115views more  BMCBI 2008»
13 years 7 months ago
Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data
Background: Time-course microarray experiments are being increasingly used to characterize dynamic biological processes. In these experiments, the goal is to identify genes differ...
Sudhakar Jonnalagadda, Rajagopalan Srinivasan