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BMCBI
2005
153views more  BMCBI 2005»
13 years 7 months ago
Mining published lists of cancer related microarray experiments: Identification of a gene expression signature having a critical
Background: Routine application of gene expression microarray technology is rapidly producing large amounts of data that necessitate new approaches of analysis. The analysis of a ...
Giacomo Finocchiaro, Francesco Mancuso, Heiko M&uu...
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
2008
102views more  BMCBI 2008»
13 years 7 months ago
Response projected clustering for direct association with physiological and clinical response data
Background: Microarray gene expression data are often analyzed together with corresponding physiological response and clinical metadata of biological subjects, e.g. patients'...
Sung-Gon Yi, Taesung Park, Jae K. Lee
GCB
2010
Springer
204views Biometrics» more  GCB 2010»
13 years 5 months ago
Learning Pathway-based Decision Rules to Classify Microarray Cancer Samples
: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...
BMCBI
2007
120views more  BMCBI 2007»
13 years 7 months ago
Re-sampling strategy to improve the estimation of number of null hypotheses in FDR control under strong correlation structures
Background: When conducting multiple hypothesis tests, it is important to control the number of false positives, or the False Discovery Rate (FDR). However, there is a tradeoff be...
Xin Lu, David L. Perkins