The research interests of the Khurana lab fall under the broad categories of genomics, computational biology and systems biology. Only about 1 percent of our DNA makes proteins, yet it has been the focus of the majority of studies in the past. Innovation in genomic technologies now allows us to interrogate the non-protein-coding parts of the genome, which has unleashed a revolution in cancer genomics. The signals from non-coding regions hold immense promise for use in cancer diagnostics and therapeutics. We use computational models and machine learning approaches to analyze and interpret the terabytes of genomic, epigenomic and transcriptomic data from cancer patients. We have used our expertise in integration of data from assays that characterize the function of DNA with the DNA sequences to develop innovative computational models that enable identification of DNA point mutations and rearrangements driving cancer growth. These models are used to analyze the growing numbers of personal genomes enabled by the decreasing costs of genome sequencing. We probe the mechanistic dynamics of non-coding regions at single-cell resolution. We are also developing novel computational algorithms that use signals from non-coding regions for early detection of cancer using non-invasive liquid biopsies.