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BMCBI
2011
13 years 9 days 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
CCS
2008
ACM
13 years 7 months ago
Measuring network security using dynamic bayesian network
Given the increasing dependence of our societies on networked information systems, the overall security of these systems should be measured and improved. Existing security metrics...
Marcel Frigault, Lingyu Wang, Anoop Singhal, Sushi...
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
14 years 5 months ago
Time and sample efficient discovery of Markov blankets and direct causal relations
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
KBSE
2005
IEEE
13 years 11 months ago
Automated population of causal models for improved software risk assessment
Recent work in applying causal modeling (Bayesian networks) to software engineering has resulted in improved decision support systems for software project managers. Once the causa...
Peter Hearty, Norman E. Fenton, Martin Neil, Patri...
BMCBI
2008
166views more  BMCBI 2008»
13 years 5 months ago
Learning transcriptional regulatory networks from high throughput gene expression data using continuous three-way mutual informa
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
Weijun Luo, Kurt D. Hankenson, Peter J. Woolf