Model order reduction for Linear Noise Approximation using time-scale separation (Extended Version)

Abstract

In this paper, we focus on model reduction of biomolecular systems with multiple time-scales, modeled using the Linear Noise Approximation. Considering systems where the Linear Noise Approximation can be written in singular perturbation form, with $\epsilon$ as the singular perturbation parameter, we obtain a reduced order model that approximates the slow variable dynamics of the original system. In particular, we show that, on a finite time-interval, the first and second moments of the reduced system are within an $O(\epsilon )$-neighborhood of the first and second moments of the slow variable dynamics of the original system. The approach is illustrated on an example of a biomolecular system that exhibits time-scale separation.

References in corpus (2)

• The validity of quasi steady-state approximations in discrete stochastic simulations
• Rigorous elimination of fast stochastic variables from the linear noise approximation using projection operators