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Using Bayesian networks to discover relations between genes, environment, and disease.

, , , and . BioData Min., (2013)

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Functional dyadicity and heterophilicity of gene-gene interactions in statistical epistasis networks., , , and . BioData Min., (2015)Using Bayesian networks to discover relations between genes, environment, and disease., , , and . BioData Min., (2013)Prediction of an outcome using NETwork Clusters (NET-C)., , , , , , , and . Comput. Biol. Chem., (2021)Estimation of environmental exposure: interpolation, kernel density estimation or snapshotting., , , , , , , and . Ann. GIS, 25 (1): 1-8 (2019)Incorporating prior expert knowledge in learning Bayesian networks from genetic epidemiological data., , , and . CIBCB, page 1-5. IEEE, (2014)Statistical Epistasis Networks Reduce the Computational Complexity of Searching Three-Locus Genetic Models., , , and . Pacific Symposium on Biocomputing, page 397-408. World Scientific Publishing, (2013)Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility., , , , , , , and . BioData Min., (2014)Bladder cancer specific pathway interaction networks., , , , and . ECAL, page 94-101. MIT Press, (2013)Copy number variation has little impact on bead-array-based measures of DNA methylation., , , , , , , , , and . Bioinform., 25 (16): 1999-2005 (2009)Detecting gene-gene interactions using a permutation-based random forest method., , , , and . BioData Min., (2016)