Scientists have realized that studying a single component of a complex biological system is sometimes not the most appropriate approach to understanding the underlying mechanisms of life.  Modeling the behavior of underlying components as well as their nonlinear interactions can often be more revealing. Such modeling requires bioinformatics tools for extracting information from experimental and observational data as well as stochastic modeling and simulation tools that statisticians, mathematicians, and engineers use to model complex systems in their own fields.  The Center for Statistical and Computational Modeling of Biological Complexity brings people with these skillsets together to make new discoveries in complex living systems.