Xia Jiang, PhD

Jiang X, Barmada MM, Cooper GF, Becich MJ. A Bayesian method for evaluating and discovering disease loci associations. PLoS ONE 6 (2011). PMID: 21853025 PMC3154195

Jiang, X., S. Visweswaran, and R.E. Neapolitan, `Mining Epistatic Interactions from High-Dimensional Data Sets Using Bayesian Networks,' in Holmes, D. and L. Jain (Eds.): Foundations and Intelligent Paradigms--3, Springer-Verlag, Berlin Heidelberg, 2011, DOI: 10.1007/978-3-642-23151-3_9

Jiang X, Barmada MM, Becich MJEvaluating de novo locus-disease discoveries in GWAS using the signal-to-noise ratio. AMIA Annu Symp Proc. 2011;2011:617-24. Epub 2011 Oct 22. PMID: 22195117 

Jiang, X., R.E. Neapolitan, M.M. Barmada, S.Visweswaran. Learning genetic epistasis using Bayesian network scoring criteria. BMC Bioinformatics; 2011: 12(89). PMCID: PMC3080825

Jiang, X., S. Visweswaran, and R.E. Neapolitan, `Mining Epistatic Interactions from High-Dimensional Data Sets Using Bayesian Networks,' in Holmes, D. and L. Jain (Eds.): Foundations and Intelligent Paradigms--3, Springer-Verlag, Berlin Heidelberg, 2011

Jiang X, Cooper GF. A Bayesian spatio-temporal method for disease outbreak detection. Journal of the American Medical Informatics Association 17 (2010) 462-471.  PMID: 20595315  PMC2995651

Jiang X, Neapolitan RE, Barmada M, Visweswaran S, Cooper GF.   A fast algorithm for learning epistatic genomic relationships.  In: Proceedings of the Annual Symposium of the American Medical Informatics Association (2010) 341-345. PMID: 21346997 PMC3041370

Jiang X, Neill DB, Cooper GF.  A Bayesian network model for spatial event surveillance. International Journal of Approximate Reasoning (2010) 51:224-239. Publication not directly supported by NIH.

Jiang, X., D.B. Neill, and G.F. Cooper,  On the robustness of Bayesian network based spatial event surveillance. International Journal of Approximate Reasoning, 51 (2010) p 224-239.  http://dx.doi.org/10.1016/j.ijar.2009.01.001

Jiang X, Neill DB, Cooper GF.  A Bayesian network model for spatial event surveillance. International Journal of Approximate Reasoning (2010) 51:224-239.  doi: ttp://dx.doi.org/10.1016/j.ijar.2009.01.001. Publication not directly supported by NIH.

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