We study the genetic basis of human diseases using computational approaches and translate this knowledge to improve patient care. With a special emphasis on incorporating functional information, evolutionary history and population structure in biomarker discovery, our research goes beyond statistical associations to seek genetic markers with strong functional impact.

  • Develop and apply computational methods to enable precision medicine
    • Biomarker discovery
    • Cancer subclonal development
    • Personalized immunotherapy
  • Discover functional elements in human genomes and the indications in diseases
    • Fine-map causal noncoding variants
    • Gene-environment interaction in complex diseases
    • Regulatory rewiring via epigenetic evolution
  • Data analytics for biomedical applications
    • Statistical support to biomedical research
    • Software, databases and analytical pipelines to facilitate “omics” studies