Pei Wang, PhD
- ASSOCIATE PROFESSOR | Genetics and Genomic Sciences
Dr. Wang received her Ph.D. in Statistics from Stanford University in 2004. Between 2004-2013, she served as a faculty in Fred Hutchinson Cancer Research Center and University of Washington, Seattle, WA. In Oct 2013, Dr. Wang joint Icahn Medical School at Mount Sinai as an Associate Professor of Genetics and Genomics. Dr. Wang’s research work has been focused on developing statistical and computational methods to address scientific questions based on data from high throughput biology/genetics experiments.
Multi-Disciplinary Training AreaGenetics and Data Science [GDS]
BS, Peking University
PhD, Stanford University
High dimensional inference & integrative genomics
I am interested in developing statistical and computational methods to address scientific questions based on data from high throughput biology/genetics experiments. The ultimate goal is to enhance our understanding of cell activities and disease initiation/progression to a system level by integrating information from diverse biological sources (genetics/genomics, proteomics, and phenotypes). Towards this goal, efforts have been made to properly model each individual type of data and to effectively characterize interactions among different biology molecules. These efforts all borrow strength from and contribute to the developments of high dimensional inference, a challenging yet thriving field in modern statistics. For more details about Dr. Wang’s research, visit http://research.mssm.edu/wanglab/
Chen LS, Prentice RL, Wang P. A penalized EM algorithm incorporating missing data mechanism for Gaussian parameter estimation. Biometrics 2014 Jan;.
Hu JK, Wang X, Wang P. Testing gene-gene interactions in genome wide association studies. Genetic epidemiology 2014 Feb; 38(2).
Danaher P, Wang P, Witten DM. The joint graphical lasso for inverse covariance estimation across multiple classes. Journal of the Royal Statistical Society. Series B, Statistical methodology 2014 Mar; 76(2).
Kennedy JJ, Abbatiello SE, Kim K, Yan P, Whiteaker JR, Lin C, Kim JS, Zhang Y, Wang X, Ivey RG, Zhao L, Min H, Lee Y, Yu MH, Yang EG, Lee C, Wang P, Rodriguez H, Kim Y, Carr SA, Paulovich AG. Demonstrating the feasibility of large-scale development of standardized assays to quantify human proteins. Nature methods 2014 Feb; 11(2).
Xu C, Wang P, Liu Y, Zhang Y, Fan W, Upton MP, Lohavanichbutr P, Houck JR, Doody DR, Futran ND, Zhao LP, Schwartz SM, Chen C, Méndez E. Integrative genomics in combination with RNA interference identifies prognostic and functionally relevant gene targets for oral squamous cell carcinoma. PLoS genetics 2013; 9(1).
Lohavanichbutr P, Méndez E, Holsinger FC, Rue TC, Zhang Y, Houck J, Upton MP, Futran N, Schwartz SM, Wang P, Chen C. A 13-gene signature prognostic of HPV-negative OSCC: discovery and external validation. Clinical cancer research : an official journal of the American Association for Cancer Research 2013 Mar; 19(5).
Li S, Hsu L, Peng J, Wang P. BOOTSTRAP INFERENCE FOR NETWORK CONSTRUCTION WITH AN APPLICATION TO A BREAST CANCER MICROARRAY STUDY. The annals of applied statistics 2013 Mar; 7(1).
Wang X, Li Q, Zhang H, Zhang Y, Li H, Wang P. A regularized multivariate regression approach for eQTL analysis. Statistics in Biosciences 2013 Nov; 10.1007/s12561-013-9106-9.