Research
Motivated by the opportunities and challenges encountered in biostatistical design and data analysis in collaborative biomedical studies, Dr. Zhou’s research focuses on the development and application of novel statistic methodologies and computational tools for the efficient design of biomedical experiments and clinical trials and rigorous analysis of large complex biomedical data such as omics data, and clustered and longitudinal data. Her interest in statistical methodology covers Bayesian hierarchical models, variable selection, model averaging, predictive modeling, and the design of clinical trials. She has developed a Bayesian hierarchical model to classify missense mutations on disease susceptibility genes, a Bayesian method to accurately estimate minimum inhibitory concentration based on growth curves, and a novel Bayesian model averaging (BMA) approach for analyzing observational gene expression and metabolomics data. She collaborates extensively with world-class biomedical researchers and clinicians at Weill Cornell Medicine (WCM) and the neighboring Memorial Sloan-Kettering Cancer Center (MSKCC) to advance cancer-related laboratory and clinical studies. She helped with the design and data analysis of numerous translational and clinical studies, including serving as the lead biostatistician to NIH-funded cancer prevention clinical trials. She led the statistical design, developed the data analysis plan, and oversaw the data analyses of a series of studies that elucidated the links between obesity, inflammation, and cancer. Her research work has been funded by NIH, NCI, DoD, and private foundations. She is also a voting member of NCI’s Cancer Prevention and Control Central IRB and a consulting biostatistical editor for the Journal of Experimental Medicine.
Currently, she is developing a user-friendly R package to extend the BMA approach to analyzing RNA-seq gene expression data and demonstrating its usage in complex observational omics data analysis and optimal designs for randomized phase II clinical trials. Her collaborative research focuses on cancer biology and novel treatments, such as radiation oncology and immunology.
Current Projects:
- Heterogeneous omics data analysis, randomized phase II trial design methods
Bio
Dr. Zhou received her PhD in statistics and decision sciences from Duke University in 2002. She worked briefly at the Genomic Institute of Novartis Research Foundation in San Diego before joining Weill Cornell Medicine in 2004. She is currently an associate professor of population health sciences at Weill Cornell Medicine and an adjunt associate professor in the Department of Statistical and Data Science at Cornell University.
Selected Publications:
- Increased trunk fat is associated with altered gene expression in breast tissue of normal weight women
- Blood Biomarkers Reflect the Effects of Obesity and Inflammation on the Human Breast Transcriptome
- Obesity promotes breast epithelium DNA damage in women carrying a germline mutation in BRCA1 or BRCA2
- Expression of the mono-ADP-ribosyltransferase ART1 by tumor cells mediates immune resistance in non-small cell lung cancer
- A Bayesian Model Averaging Approach for Observational Gene Expression Studies