My research focuses on understanding complex human diseases by undertaking integrative approaches, which combine biology, computational and statistical learning, bioinformatics, and genomics. In particular, I am interested in developing computational algorithms, software and tools
- to help identify genetic and regulatory mechanisms underlying human diseases, so that we can better understand why different genetic and gene expression changes in patients can lead to different disease phenotypes;
- to identify biomarkers, and classify and diagnose various human diseases using metadata (e.g., genetic, gene expression and phenotypic data); and
- to predict outcomes of patients with human diseases using metadata.
My current work involves:
- subphenotyping asthma patients using computational approaches, and
- understanding breast cancer mechanisms using dynamic network learning approaches.