A central premise of systems biology rests upon the idea that intracellular molecular dynamics are, to some extent, subject to formal mathematical description. Our work exemplifies this through the measurement of rates of endogenous protein dynamics in single cells. We have derived a method whereby rates and rate dependencies are extracted from single cell fluorescence microscopy measurements from populations that are at steady state (unsynchronized proliferating cells). We use several differentially labeled antibodies and record microscopic images from 10,000 cells within up to 3 cellular compartments. Our formalism allows to couple measured probability densities with rates, using Gauss flux theorem. This provides a route to infer signal transduction dynamics, e.g. in cell cycle or in pathways of DNA damage, based on parallelized static measurements.
