Associate Professor, Biochemistry and Molecular Genetics
- BS, Microwave Engineering, University of California, Los Angeles
- PhD, Statistical Physics, University of California, Santa Barbara
- Postdoc, Statistical Physics, University of Maryland
- Postdoc, Computational Biology, The Rockefeller University
Physical Modeling of Microarray Hybridization; Analysis of Genomic Tiling Array Data; Bioinformatics; Computational Biology; Regulatory Networks
We are interested in characterizing the complex epigenetic regulatory network of histone modifications and DNA methylation, which exhibits extensive cross-talk. We apply machine-learning methods including Multivariate Regression Splines (MARS) and Bayesian Networks (BN) to epigenomic data in order to uncover this network and understand how it regulates transcription and DNA replication. We analyze both publicly available data sets (e.g., epigenomic data generated by K. Zhao's lab and the ENCODE, modENCODE and Epigenomics Mapping Consortia) as well as data generated by colleagues here at UVa. In our collaborations, we are studying (1) preinitiation complex (PIC) and transcription factor dynamics and their role in regulation of transcription level and precision (2) epigenomic regulation of the epithelial to mesenchymal transition -- a model of how cells are reprogrammed during metastasis (3) origins of DNA replication in the human genome and the epigenetic factors that drive them (4) the role of histone deacetylaces including Sir2 in aging and (5) the impact of chemicals in our environment (e.g., Bisphenol A) on our epigenome and subsequent phenotypic outcomes. An exciting aspect of the collaborative environment at UVa is that we are able to experimentally test our predicted epigenetic regulatory network models at the biochemical and phenotypic level.