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» Scalable Rule-Based Gene Expression Data Classification
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ICDE
2008
IEEE
195views Database» more  ICDE 2008»
14 years 6 months ago
Scalable Rule-Based Gene Expression Data Classification
Abstract-- Current state-of-the-art association rule-based classifiers for gene expression data operate in two phases: (i) Association rule mining from training data followed by (i...
Mark A. Iwen, Willis Lang, Jignesh M. Patel
CIBB
2008
13 years 6 months ago
Mining Association Rule Bases from Integrated Genomic Data and Annotations
During the last decade, several clustering and association rule mining techniques have been applied to highlight groups of coregulated genes in gene expression data. Nowadays, inte...
Ricardo Martínez, Nicolas Pasquier, Claude ...
BIRD
2007
Springer
154views Bioinformatics» more  BIRD 2007»
13 years 11 months ago
Mining Spatial Gene Expression Data for Association Rules
Abstract. We analyse data from the Edinburgh Mouse Atlas GeneExpression Database (EMAGE) which is a high quality data source for spatio-temporal gene expression patterns. Using a n...
Jano I. van Hemert, Richard A. Baldock
BMCBI
2007
173views more  BMCBI 2007»
13 years 4 months ago
Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data
Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
WCE
2007
13 years 5 months ago
Gene Selection for Tumor Classification Using Microarray Gene Expression Data
– In this paper we perform a t-test for significant gene expression analysis in different dimensions based on molecular profiles from microarray data, and compare several computa...
Krishna Yendrapalli, Ram B. Basnet, Srinivas Mukka...