Applied Mathematics Colloquium: Dr. Hye-Won Kang

Title: Quasi-steady-state approximations of the stochastic enzyme kinetics model

Speaker: Hye-Won Kang, UMBC

Abstract: Quasi-steady-state approximations (QSSAs) are useful tools to reduce complex biochemical networks and to derive their approximate models with the simpler structure. However, we need to be careful to apply these approximations to general biochemical networks, since the approximations are valid for specific parameter ranges. QSSAs have been widely studied in the deterministic setting by multiple authors, and several conditions for their validity have been proposed. In this talk, we consider the stochastic Michaelis-Menten enzyme kinetics model and derive several quasi-steady-state approximations. In particular, we consider the standard QSSA (sQSSA), the total QSSA (tQSSA), and the reverse QSSA (rQSSA). We use multiscaling techniques and derive a simple set of conditions under which these QSSA systems are exact large-volume limits of the underlying stochastic kinetic network. This is joint work with Wasiur KhudaBukhsh, Heinz Koeppl, and Grzegorz Rempala.