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» Mining phenotypes and informative genes from gene expression...
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CANDC
2005
ACM
13 years 7 months ago
Gene selection from microarray data for cancer classification - a machine learning approach
A DNA microarray can track the expression levels of thousands of genes simultaneously. Previous research has demonstrated that this technology can be useful in the classification ...
Yu Wang 0008, Igor V. Tetko, Mark A. Hall, Eibe Fr...
BMCBI
2011
13 years 2 months ago
Using Stochastic Causal Trees to Augment Bayesian Networks for Modeling eQTL Datasets
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
Kyle C. Chipman, Ambuj K. Singh
ICDE
2008
IEEE
195views Database» more  ICDE 2008»
14 years 9 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
BMCBI
2011
12 years 11 months ago
RegNetB: Predicting Relevant Regulator-Gene Relationships in Localized Prostate Tumor Samples
Background: A central question in cancer biology is what changes cause a healthy cell to form a tumor. Gene expression data could provide insight into this question, but it is dif...
Angel Alvarez, Peter J. Woolf
ISMB
2000
13 years 9 months ago
Genes, Themes, and Microarrays: Using Information Retrieval for Large-Scale Gene Analysis
The immensevolumeof data resulting from DNAmicroarray experiments, accompaniedby an increase in the numberof publications discussing gene-related discoveries, presents a majordata...
Hagit Shatkay, Stephen Edwards, W. John Wilbur, Ma...