Research Interests

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.

In the news:

• March 2014: CMU press release about the asthma phenotyping project by using machine learning approaches - joint work with Dr. Sally Wenzel at UPMC and the SARP team. Also in:
  • CMU Homepage Stories
  • Pittsburgh's NPR News Station, WESA 90.5
  • Pittsburgh Post-Gazette
  • Biomedical Beat, National Institute of General Medical Sciences, NIH
• July 2014: CMU press release about breast cancer work by using dynamic network approach - joint work with Dr. Eric Xing's lab at CMU and Dr. Mina Bissell's lab at Lawrence Berkeley National Lab.