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RECOMB
2000
Springer
13 years 11 months ago
Using Bayesian networks to analyze expression data
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a "snapshot" of transcription levels within the c...
Nir Friedman, Michal Linial, Iftach Nachman, Dana ...
IJAR
2007
130views more  IJAR 2007»
13 years 7 months ago
Bayesian network learning algorithms using structural restrictions
The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domai...
Luis M. de Campos, Javier Gomez Castellano
KES
2007
Springer
14 years 1 months ago
Predictive and Contextual Feature Separation for Bayesian Metanetworks
Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, dep...
Vagan Y. Terziyan
CIDM
2009
IEEE
14 years 2 months ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...
SEMWEB
2005
Springer
14 years 1 months ago
A Bayesian Network Approach to Ontology Mapping
This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling ...
Rong Pan, Zhongli Ding, Yang Yu, Yun Peng