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BMCBI
2007
135views more  BMCBI 2007»
13 years 4 months ago
Detecting multivariate differentially expressed genes
Background: Gene expression is governed by complex networks, and differences in expression patterns between distinct biological conditions may therefore be complex and multivariat...
Roland Nilsson, José M. Peña, Johan ...
BMCBI
2008
159views more  BMCBI 2008»
13 years 4 months ago
Multivariate hierarchical Bayesian model for differential gene expression analysis in microarray experiments
Background: Identification of differentially expressed genes is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increas...
Hongya Zhao, Kwok-Leung Chan, Lee-Ming Cheng, Hong...
BMCBI
2005
152views more  BMCBI 2005»
13 years 4 months ago
CoPub Mapper: mining MEDLINE based on search term co-publication
Background: High throughput microarray analyses result in many differentially expressed genes that are potentially responsible for the biological process of interest. In order to ...
Blaise T. F. Alako, Antoine Veldhoven, Sjozef van ...
BMCBI
2005
144views more  BMCBI 2005»
13 years 4 months ago
GeneRank: Using search engine technology for the analysis of microarray experiments
Background: Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the t...
Julie L. Morrison, Rainer Breitling, Desmond J. Hi...
BMCBI
2007
159views more  BMCBI 2007»
13 years 4 months ago
Detecting differential expression in microarray data: comparison of optimal procedures
Background: Many procedures for finding differentially expressed genes in microarray data are based on classical or modified t-statistics. Due to multiple testing considerations, ...
Elena Perelman, Alexander Ploner, Stefano Calza, Y...