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» A Repulsive Clustering Algorithm for Gene Expression Data
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WILF
2005
Springer
112views Fuzzy Logic» more  WILF 2005»
14 years 1 months ago
NEC for Gene Expression Analysis
Aim of this work is to apply a novel comprehensive machine learning tool for data mining to preprocessing and interpretation of gene expression data. Furthermore, some visualizatio...
Roberto Amato, Angelo Ciaramella, N. Deniskina, Ca...
BMCBI
2007
182views more  BMCBI 2007»
13 years 7 months ago
EDISA: extracting biclusters from multiple time-series of gene expression profiles
Background: Cells dynamically adapt their gene expression patterns in response to various stimuli. This response is orchestrated into a number of gene expression modules consistin...
Jochen Supper, Martin Strauch, Dierk Wanke, Klaus ...
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,...
FGCN
2008
IEEE
155views Communications» more  FGCN 2008»
13 years 9 months ago
Modeling the Marginal Distribution of Gene Expression with Mixture Models
We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...
Edward Wijaya, Hajime Harada, Paul Horton
BMCBI
2008
179views more  BMCBI 2008»
13 years 7 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