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 and applying 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:
- phenotyping asthma patients using computational approaches;
- understanding regulatory mechanisms of different subtypes of asthma using systems biology and machine learning approaches;
- transcriptome-wide screening of expression traits and molecular markers for drug abuse using machine learning approach;
- genome-wide discovery of new drug targets for drug abuse and their epistatic genetic influences via structured association mapping.
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