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BMCBI
2010
181views more  BMCBI 2010»
13 years 7 months ago
Intensity dependent estimation of noise in microarrays improves detection of differentially expressed genes
Background: In many microarray experiments, analysis is severely hindered by a major difficulty: the small number of samples for which expression data has been measured. When one ...
Amit Zeisel, Amnon Amir, Wolfgang J. Köstler,...
BMCBI
2004
150views more  BMCBI 2004»
13 years 7 months ago
Rank Difference Analysis of Microarrays (RDAM), a novel approach to statistical analysis of microarray expression profiling data
Background: A key step in the analysis of microarray expression profiling data is the identification of genes that display statistically significant changes in expression signals ...
Dietmar E. Martin, Philippe Demougin, Michael N. H...
BMCBI
2007
135views more  BMCBI 2007»
13 years 7 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
2010
165views more  BMCBI 2010»
13 years 7 months ago
Filtering, FDR and power
Background: In high-dimensional data analysis such as differential gene expression analysis, people often use filtering methods like fold-change or variance filters in an attempt ...
Maarten van Iterson, Judith M. Boer, Renée ...
BMCBI
2004
150views more  BMCBI 2004»
13 years 7 months ago
Graph-based iterative Group Analysis enhances microarray interpretation
Background: One of the most time-consuming tasks after performing a gene expression experiment is the biological interpretation of the results by identifying physiologically impor...
Rainer Breitling, Anna Amtmann, Pawel Herzyk