Statistical Genomics

Our Approach

Our research questions can be approached through a series of estimation, extensive computer simulations, and statistical testing and prediction problems.

Each of these problems require developing new theoretical models that can best represent the data and also implementing new software tools for scalable analysis of millions of observations simultaneously.

Research Areas


    • Deleterious mutations and lifetime effects of inbreeding
    • Metabolic and Cardiovascular disease
    • Novel Inference from Biobank Data

    Common diseases

    • Obesity
    • Type 2 Diabetes
    • Hypertension
    • Trans-Ancestry Genomics

    Into the future

    • Evolution of mating system in humans
    • Theory for Statistical Genetics Inference
    • Trans-Ancestry Genomics
    • Efficient computation in large scale biobank (hybrid computing)


          Our Team

          Group leader



          • Ms Ying Wang

            Higher degree by research (PhD) student
            Institute for Molecular Bioscience