Xiang Zhou is an Assistant Professor of Biostatistics. He received his M.S. in Statistics and Ph.D. in Neurobiology from Duke University in 2010, and completed a postdoctoral training at the University of Chicago afterwards. He was a William H. Kruskal Instructor in the Department of Statistics at the University of Chicago before he joined the faculty at the University of Michigan in 2014. His research focuses on developing statistical and computational methods in large-scale genetic and functional genomic studies to understand the genetic basis of phenotypic variation for various quantitative traits and complex diseases.
- Ph.D., Neurobiology, Duke University, 2010
- M.S., Statistics, Duke University, 2009
- B.S., Biology, Peking University, 2004
- Xiang Zhou and Matthew Stephens. (2014). Efficient algorithms for multivariate mixed models in genome-wide association studies. Nature Methods. 407-409..
- Xiang Zhou, Peter Carbonetto and Matthew Stephens. (2013). Polygenic modeling with Bayesian sparse linear mixed models. PLoS Genetics e1003264..
- Xiang Zhou and Matthew Stephens. (2012). Genome-wide efficient mixed-model analysis for association studies. Nature Genetics 821-824..
- Xiang Zhou, Liangli Wang, Hiroshi Hasegawa, Priyanka Amin, Bao-Xia Han, Shinjiro Kaneko, Youwen He and Fan Wang. (2010). Deletion of PIK3C3/Vps34 in sensory neurons causes rapid neurodegeneration by disrupting the endosomal but not the autophagic pathway. Proc Natl Acad Sci U.S.A. 9424-9429..
- Xiang Zhou and Jerome Reiter. (2010). A note on Bayesian inference after multiple imputation. The American Statistician 159-163..
- Xiang Zhou, J Ramesh Babu, Susana da Silva, Qing Shu, Isabella A. Graef, Tim Oliver, Toshifumi Tomoda, Marie W. Wooten and Fan Wang. (2007). Unc-51-like kinase 1/2-mediated endocytic processes regulate filopidia extension and branching of sensory axons. Proc Natl Acad Sci U.S.A. 5842-5847..