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» Bayesian Networks Learning for Gene Expression Datasets
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KDD
2005
ACM
130views Data Mining» more  KDD 2005»
15 years 10 months ago
Simple and effective visual models for gene expression cancer diagnostics
In the paper we show that diagnostic classes in cancer gene expression data sets, which most often include thousands of features (genes), may be effectively separated with simple ...
Gregor Leban, Minca Mramor, Ivan Bratko, Blaz Zupa...
ECAL
2003
Springer
15 years 2 months ago
Evolving Fractal Gene Regulatory Networks for Robot Control
Fractal proteins are a new evolvable method of mapping genotype to phenotype through a developmental process, where genes are expressed into proteins comprised of subsets of the Ma...
Peter J. Bentley
70
Voted
ISNN
2005
Springer
15 years 3 months ago
An Information Criterion for Informative Gene Selection
It is important in bioinformatics research and applications to select or discover informative genes of a tumor from microarray data. However, most of the existing methods are based...
Fei Ge, Jinwen Ma
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
15 years 10 months ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher
ICML
2004
IEEE
15 years 10 months ago
Learning Bayesian network classifiers by maximizing conditional likelihood
Bayesian networks are a powerful probabilistic representation, and their use for classification has received considerable attention. However, they tend to perform poorly when lear...
Daniel Grossman, Pedro Domingos