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» CoXpress: differential co-expression in gene expression data
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BMCBI
2008
126views more  BMCBI 2008»
14 years 11 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»
14 years 11 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»
14 years 11 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
15 years 24 days 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»
14 years 11 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