Active researh grants:
NIH/NIGMS R01-GM122078: "Statistical Models for Genetic Studies Using Network and Integrative Analysis" (PI: Chung)
NIH/NCI R21-CA209848: "Algorithms for Literature-Guided Multi-Platform Identification of Cancer Subtypes" (PI: Chung & Kelemen)
My primary research interest is to address challenges and opportunities arising from modern complex genomic data and to promote understanding of mechanism of development and progression of diseases using statistical approaches. My current research focuses on the following directions:
Integrative analysis of biomedical big data:
I am pursuing development of statistical framework that improves biological understanding of risk and progression of diseases, by integrating various types of high throughput genetic and genomic data profiled in diverse tissues and cell lines, along with information available in public databases. Currently, I focus on the development of novel statistical methods for genome-wide association studies (GWAS) and cancer genomics. As a part of these two projects, I am also developing a statistical framework for text mining of biomedical literature. These two projects are supported by the NIH R01 and R21 research grants (see above), respectively, and I am also currently actively participating the Informatics Technology for Cancer Research (ITCR) Initiative for the cancer genomics research project.
Analysis of high throughput sequencing data:
I am pursuing development of statistical methodology and software to analyze high throughput sequencing (HTS) data, which has revolutionized biomedical research. Specifically, I am interested in investigating optimal design and unbiased analysis of HTS experiments, with special focus on ChIP-Seq. I am also interested in developing novel statistical methods to effectively utilize information unique to each of newly emerging applications of HTS technology, such as CLIP-Seq, ChIP-exo, and Hi-C, among others. I have also recently worked with the Encyclopedia of DNA Elements (ENCODE) Consortium for the optimal design and statistical analysis of ChIP-Seq, investigating the transcription factor-DNA interaction and the histone modifications.
Check here for the list of my publications.