The regulatory networks of bacteria play a key role in their information processing capabilities, coordinating and executing interactions with their environments. Quantitative, predictive models of these networks would be tremendously beneficial for facilitating the development of new antimicrobial therapies, enabling synthetic biology applications, and understanding bacterial evolution and ecology. Ultimately, the aim of my laboratory is to build a multiscale framework enabling modeling of bacterial regulatory networks at any level of detail, from atomistic to cellular. To this end, we develop and apply high-throughput experimental methods for measuring biomolecular interactions and cellular regulatory states in vivo, and for profiling the phenotypic consequences of regulatory changes. In tandem with these experimental approaches, we use molecular simulation and mathematical modeling to obtain high-resolution insight into the biomolecular interactions driving regulatory networks, and the systems-level effects of altering them.