My research has focused on omics studies, bioinformatics and mathematical modeling to study cancer for the purpose of understanding cancer biology as well as to discover clinical biomarkers. We are especially interested in designing novel experimental and computational methods to dissect 3-D chromatin interactions and how the disordered interactions (and epigenetic modifications) are associated with cancer/disease development. We have designed several methods/pipelines/database for omics data integration, deciphering cancer driver genes and pathways, and analysis of chromatin interaction data. We have also designed several mathematical models/methods to not only analyze next-generation sequencing data (bulk and single cell data), but also to understand biological mechanisms by using Bayesian statistics, network optimization and machine learning.