This talk will present new statistical tools for analyzing single-particle tracking data from thousands of individual fluorescent proteins in liv-ing cells. These methods optimally sort individual protein tracks from a large population of tracks into discrete diffusive states, each of which may correspond to a different biochemical state. Application of these methods can also reveal transitions among the different states found, offering the prospect of eventually being able to characterize biochemistry and systems biology in individual living cells.