Ph.D., McMaster University, 2014
M.Sc., Beijing Normal University, 2009
B.Sc., Zhengzhou University, 2006
Cold Spring Harbor Laboratory, 2015-2018
University of British Columbia, 2014-2015
Millions of genetic variants have been identified in human genomes and the catalog of genetic variation is still expanding rapidly due to the continual drop of sequencing costs. Understanding the functional, clinical, and evolutionary significance of genetic variants has become a central question in biology and precision medicine. However, it is very challenging to distinguish important variants from neutral ones. Therefore, many genetic variants in patients’ genomes are marked as “variant of uncertain significance”, forming a major hurdle for both basic research and medical practice.
I am interested in addressing the problem of “variant of uncertain significance” by unifying evolutionary biology and machine learning. My research is motivated by the insight that evolution operates like a high-throughput mutagenesis experiments: deleterious mutations are quickly purged from populations due to natural selection, which in turn leaves detectable marks on human genomic sequences. I have developed multiple machine learning and statistical frameworks to identify the signatures of deleterious variants from population and functional genomic data. Not only have these computational methods provided useful insights into human evolution but also have been applied to prioritize causal variants associated with human genetic disorders.