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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)Incorporating prior expert knowledge in learning Bayesian networks from genetic epidemiological data., , , and . CIBCB, page 1-5. IEEE, (2014)Bladder cancer specific pathway interaction networks., , , , and . ECAL, page 94-101. MIT Press, (2013)Enabling Personal Genomics with an Explicit Test of Epistasis., , , , , , , and . Pacific Symposium on Biocomputing, page 327-336. World Scientific Publishing, (2010)Semi-supervised recursively partitioned mixture models for identifying cancer subtypes., , , , , , , and . Bioinform., 26 (20): 2578-2585 (2010)Supervising Random Forest Using Attribute Interaction Networks., , , , , and . EvoBIO, volume 7833 of Lecture Notes in Computer Science, page 104-116. Springer, (2013)Model-based clustering of DNA methylation array data: a recursive-partitioning algorithm for high-dimensional data arising as a mixture of beta distributions., , , , , , , , , and 1 other author(s). BMC Bioinform., (2008)Analysis of High-throughput DNA Methylation Bead Arrays Utilizing Bayesian Genotyping Algorithms., , , , , , , , , and 3 other author(s). BMEI (1), page 447-452. IEEE Computer Society, (2008)