The research interests of the Khurana lab fall under the broad categories of genomics, computational biology and systems biology. We use computational models and machine learning approaches to analyze and interpret the terabytes of genomic, epigenomic and transcriptomic data from cancer patients. Our goal is to identify the genetic and epigenetic changes that enable initial tumor growth, and resistance to treatment in later stages. Towards this goal, we also develop computational methods that enable us to detect and monitor tumor genomic and epigenomic changes in minimally invasive manner using cell-free DNA whole-genome sequencing, as well as methods that leverage digital histopathology to infer tumor molecular states and disease progression. We also develop strategies for treatment of the new subtypes of tumors that we have identified, for example stem cell-like castration-resistant prostate cancer, using targeted and immunotherapeutic approaches. Our current focus is on prostate and breast cancers.