Research in the Mallick lab centers on developing and applying multi-scale systems approaches to enable personalized, predictive medicine in cancer. Specifically, we are developing computational methods and experimental techniques to identify diagnostic and prognostic circulating biomarkers. Biomarker-based approaches to detect cancers as early as possible and to personalize treatment are envisioned to radically improve patient outcomes and reduce healthcare costs. Within our multi-scale framework, one can consider biomarkers to be host-scale variables that inform tumor and cell-scale phenomena. Our approach to marker discovery begins with the development of molecular/cellular-scale models that attempt to describe how cells are likely to behave in response to endogenous (mutation) or exogenous perturbation (therapeutics). At the tumor-scale, we are investigating tumor heterogeneity and evolution. Recently, we have been interrogating the role of tumor-microenvironment in directing tumor evolution. At the host-scale, we are attempting to model the relationship between the tumor and the circulating proteomes to help inform biomarker candidate selection. Together, these inquiries will enable us to better understand cancer and to enable rational, model-driven approaches to biomarker discovery.