A major difficulty for understanding biological systems is that they span a broad range of scales. My lab aims to connect the microscopic (e.g., genetic or molecular) level to the macroscopic (e.g., phenotypic) level using mathematical and computational tools. One problem in bridging this gap is that direct modeling at the microscopic level is extremely difficult. My approach is to develop and analyze models at an intermediate mesoscopic level that are biophysically informed by the microscopic level but are simple enough to make quantitative predictions at the macroscopic level. This can also be applied in reverse, where the macroscopic level provides constraints on the mesoscopic level that can then isolate the key components at the microscopic level. When the appropriate mathematical and computational tools do not exist, I develop new ones. My research is thus divided between purely theoretical research and applied work in collaboration with experiments on topics in metabolism, gene transcription, human genetics, and neuroscience.