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个人简介
Dr. Zhou’s research interest is to develop and apply novel statistical methods to better design biological and clinical studies related to cancer prevention, diagnosis and treatment and properly analyze data generated from such studies. Specifically, her interest in statistical methodology covers hierarchical model development, variable selection, model averaging, predictive modeling and the analysis of large complex datasets. She developed a Bayesian hierarchical model to classify missense mutations on disease susceptibility genes (Journal of the American Statistical Association, 100: 51-60), made significant contributions to the development of a Bayesian method to accurately estimate minimum inhibitory concentration based on high throughput microbial growth curves generated from automated microbial susceptibility systems (Annals of Applied Statistics, 3[2]: 710-730), and developed a novel Bayesian model averaging (BMA) approach for analyzing observational gene-expression data (Annals of Applied Statistics, 6[2]: 497-520). She is currently applying the BMA approach to the analysis of metabolomic data derived from mouse and human samples. Her methodology research has been funded by NIH/NCI and the CTSC.
研究兴趣
论文共 40 篇作者统计合作学者相似作者
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Carmen R. Ferrara, Ji Dong K. Bai, Erin M. McNally, Gregory G. Putzel,Xi Kathy Zhou, Hanhan Wang, Alan Lang, Deborah Nagle, Paula Denoya, Jan Krumsiek,Andrew J. Dannenberg, David C. Montrose
crossref(2023)
David C. Montrose,Xi Kathy Zhou,Levy Kopelovich,Rhonda K. Yantiss, Edward D. Karoly,Kotha Subbaramaiah,Andrew J. Dannenberg
crossref(2023)
crossref(2023)
David C. Montrose,Xi Kathy Zhou,Erin M. McNally,Erika Sue,Rhonda K. Yantiss,Steven S. Gross, Nitai D. Leve,Edward D. Karoly, Chen S. Suen,Lilan Ling,Robert Benezra,Eric G. Pamer,
crossref(2023)
Cancer Prevention Researchno. 6 (2022): 407-407
CANCER DISCOVERYno. 5 (2021): 1306-1306
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