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» A Repulsive Clustering Algorithm for Gene Expression Data
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TCBB
2008
107views more  TCBB 2008»
13 years 9 months ago
Coclustering of Human Cancer Microarrays Using Minimum Sum-Squared Residue Coclustering
It is a consensus in microarray analysis that identifying potential local patterns, characterized by coherent groups of genes and conditions, may shed light on the discovery of pre...
Hyuk Cho, Inderjit S. Dhillon
BMCBI
2006
153views more  BMCBI 2006»
13 years 9 months ago
Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments
Background: The small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating v...
Maureen A. Sartor, Craig R. Tomlinson, Scott C. We...
CSB
2005
IEEE
143views Bioinformatics» more  CSB 2005»
14 years 2 months ago
Multivariate gene selection: Does it help
When building predictors of disease state based on gene expression data, gene selection is performed in order to achieve a good performance and to identify a relevant subset of ge...
Carmen Lai, Marcel J. T. Reinders
NAR
2008
175views more  NAR 2008»
13 years 9 months ago
Onto-CC: a web server for identifying Gene Ontology conceptual clusters
The Gene Ontology (GO) vocabulary has been extensively explored to analyze the functions of coexpressed genes. However, despite its extended use in Biology and Medical Sciences, t...
Rocío Romero-Záliz, Coral del Val, J...
JUCS
2007
118views more  JUCS 2007»
13 years 9 months ago
A Model of Immune Gene Expression Programming for Rule Mining
: Rule mining is an important issue in data mining. To address it, a novel Immune Gene Expression Programming (IGEP) model was proposed. Concepts of rule, gene, immune cell, and an...
Tao Zeng, Changjie Tang, Yong Xiang, Peng Chen, Yi...