7347646743

Applications:
Genetics, Genomics
Methodologies:
Bayesian Methods, Causal Inference, High-Dimensional Data Analysis, Machine Learning, Statistical Inference, Statistical Modeling

Xiaoquan William Wen

Professor

Department of Biostatistics

Xiaoquan (William) Wen is an Associate Professor of Biostatistics. He received his PhD in Statistics from the University of Chicago in 2011 and joined the faculty at the University of Michigan in the same year. His research centers on developing Bayesian and computational statistical methods to answer interesting scientific questions arising from genetics and genomics.

In the applied field,  he is  particularly interested in seeking statistically sound and computationally efficient solutions to scientific problems in the areas of genetics and functional genomics.
Quantifying tissue-specific expression quantitative trait loci (eQTLs) via Bayesian model comparison

Quantifying tissue-specific expression quantitative trait loci (eQTLs) via Bayesian model comparison