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» Gene set analysis for longitudinal gene expression data
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BMCBI
2005
141views more  BMCBI 2005»
13 years 8 months ago
Construction and validation of the APOCHIP, a spotted oligo-microarray for the study of beta-cell apoptosis
Background: Type 1 diabetes mellitus (T1DM) is a autoimmune disease caused by a long-term negative balance between immune-mediated beta-cell damage and beta-cell repair/regenerati...
Nils E. Magnusson, Alessandra K. Cardozo, Mogens K...
BMCBI
2010
158views more  BMCBI 2010»
13 years 9 months ago
Validation of differential gene expression algorithms: Application comparing fold-change estimation to hypothesis testing
Background: Sustained research on the problem of determining which genes are differentially expressed on the basis of microarray data has yielded a plethora of statistical algorit...
Corey M. Yanofsky, David R. Bickel
ESANN
2008
13 years 10 months ago
A method for robust variable selection with significance assessment
Our goal is proposing an unbiased framework for gene expression analysis based on variable selection combined with a significance assessment step. We start by discussing the need ...
Annalisa Barla, Sofia Mosci, Lorenzo Rosasco, Ales...
BMCBI
2010
214views more  BMCBI 2010»
13 years 9 months ago
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
Background: Clustering the information content of large high-dimensional gene expression datasets has widespread application in "omics" biology. Unfortunately, the under...
Aaron M. Newman, James B. Cooper
BMCBI
2010
181views more  BMCBI 2010»
13 years 9 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,...