Biochemical reaction networks, e.g. of metabolic type, may comprise hundreds of species and reactions. On the other hand, reactions are typically not expressed in an elementary form: their rates are consequently not in mass-action form but they involve more parameters as e.g. Michaelis-Menten kinetics.

In this talk, I present an approach to understand the possible range dynamics of such networks, which exploits the parameter richness of the reaction rates. At a fixed equilibrium, we rescale the partial derivatives appearing in the Jacobian to highlight change of stabilities and bifurcations, with consequent nearby dynamics. In essence, we identify fast `leading’ subnetworks that drives the dynamics into an unstable region, causing the occurrence of specific bifurcations.