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» Analysis of variance components in gene expression data
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BMCBI
2010
153views more  BMCBI 2010»
14 years 10 months ago
GOAL: A software tool for assessing biological significance of genes groups
Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...
BMCBI
2007
143views more  BMCBI 2007»
14 years 10 months ago
Factor analysis for gene regulatory networks and transcription factor activity profiles
Background: Most existing algorithms for the inference of the structure of gene regulatory networks from gene expression data assume that the activity levels of transcription fact...
Iosifina Pournara, Lorenz Wernisch
ESANN
2008
14 years 11 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
2002
89views more  BMCBI 2002»
14 years 9 months ago
Sources of variability and effect of experimental approach on expression profiling data interpretation
Background: We provide a systematic study of the sources of variability in expression profiling data using 56 RNAs isolated from human muscle biopsies (34 Affymetrix MuscleChip ar...
Marina Bakay, Yi-Wen Chen, Rehannah H. A. Borup, P...
BMCBI
2008
179views more  BMCBI 2008»
14 years 10 months ago
Building pathway clusters from Random Forests classification using class votes
Background: Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bri...
Herbert Pang, Hongyu Zhao