Xia Jiang, PhD

Lee S, Jiang X. Modeling miRNA-mRNA interactions that cause phenotypic abnormality in breast cancer patients. PLOS One. Online 9 August 2017.

Rathnam C, Lee S, Jiang X. An algorithm for direct causal learning of influences on patient outcomes. Artif Intell Med. 2017 Jan; 75: 1-15. doi: 10.1016/j.artmed.2016.10.003. Epub 2016 Nov 5. PMID: 28363452. PMC ID: PMC5415921

Jiang X, Neapolitan RE. LEAP: biomarker inference through learning and evaluating association patterns. Genetic Epidemiology. 2015; 39(3):173–184. PMID: 25677188. PMCID: PMC4366363.

Neapolitan RE, Jiang X. Study of integrated heterogeneous data reveals prognostic power of gene expression for breast cancer survival. PLoS ONE. 2015; 10 (2): DOI: 10.1371/journal.pone.0117658. PMID: 25723490. PMCID: PMC4344205.

Jiang X, Jao J, Neapolitan RE. Learning predictive interactions using information gain and Bayesian network scoring. PLoS ONE. 2015; 10(12): e0143247. doi:10.1371/journal.pone.0143247. PMCID: PMC4666609.

Jiang X, Visweswaran S, Neapolitan RE. Scoring and Searching Bayesian Network Models of Gene-Phenotype Association. In: Sinoquet C, Mourad R, editors. Probabilistic Graphical Models for Genetics, Genomics and Postgenomics. Oxford University Press, 2014.

Neapolitan RE, Jiang X. A Note of Caution on Maximizing Entropy. Entropy. 2014; 16 (7):4004-14. doi: 10.3390/e16074004.

Neapolitan RE, Xue D, Jiang X. Modeling the Altered Expression Levels of Genes on Signaling Pathways in Tumors as Causal Bayesian Networks. Cancer Informatics. 2014; 13:77-84. PMCID: PMC4051800. doi: 10.4137/CIN.S13578.

Jiang X, Cai B, Xue D, Lu X, Cooper GF, Neapolitan RE. A comparative analysis of methods for predicting clinical outcomes using high-dimensional genomic datasets. Journal of the American Medical Informatics Association (2014). Oct;21(e2):e312-9. doi: 10.1136/amiajnl-2013-002358. Epub 2014 Apr 15. PMID: 24737607. PMC4173174.

^