Systems Biology seeks to understand how a biological system operates as a whole by measuring, modeling, and probing interactions between components in the system (e.g., genes, proteins, metabolites) rather than studying the components in isolation. To gain such an understanding, systems biology studies follow an iterative approach of collecting quantitative experimental data, computational and statistical modeling of these data, and implementing these models to make predictions in new experimental conditions. These studies can guide the next set of experiments to better model and understand how a system functions via the interaction of its parts. Example biological systems analyzed by these methods include cellular signaling networks in microbial cells, dynamic processes during viral infection, and multi-cellular interactions in animal models and human patients; each system of study presents unique opportunities and challenges in collecting, analyzing and modeling the data. The resulting understanding gained from these studies can impact disease therapy (e.g., identifying new drug targets or biomarkers), biotechnology applications (e.g., determining methods to optimize biofuel production), as well as our general understanding of how biological networks operate. Students working in the research groups within the Systems Biology focus group will have the unique opportunity to work in a highly collaborative environment and gain inter-disciplinary training in both biological and computational fields.