Inference of analytical thermodynamic models for biological networks

► We present algorithm for inferring dynamical models of closed biochemical mixtures. ► The approach does not require prior knowledge on the underlying mechanism structure. ► As input, a cloud of steady states, and a time series of measurements are utilized. ► Both Michaelis-Menten and MAPK cascade mechanisms are used for validation purposes.