Associate Professor of Computational Biology and Bioinformatics
Associate Professor, Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute
Affiliated Faculty Member, Harvard Stem Cell Institute
We develop statistical and computational methodologies for genomic data analysis and integration, with the aim to understand systems-level gene regulatory mechanisms. More specifically, our research has been focused on epigenomics. A multi-cellular organism contains only one genome, but different cell types contain different epigenomic patterns: chromatin structure, histone modification, and DNA methylations. These epigenomic marks are important for regulating protein-DNA binding activities and gene transcription.
Current projects include: (1) Developing methods for gene regulatory network inference by integrating genomic and epigenomic data; (2) Developing methods for characterizing the combinatorial chromatin state from ChIPseq data; (3) Developing methods for single-cell gene expression data analysis; (4) Developing methods for interrogating the connection between genomic and epigenomic variations; (5) Using systems biology approaches to characterize the gene regulatory networks underlying stem cell maintenance and cell-fate transition; (6) Using systems biology approach to characterize the biological functions of genetic variants associated with cancer and lung diseases. We collaborate closely with both basic biologists and clinicians in Harvard Medical School.
Ph.D., 1999, Mathematics, University of Maryland at College Park