Abstract

Variability and heterogeneity are fundamental features of microbial production systems. The overall variability is affected by intrinsic, extrinsic and external noise leading to large variations of individual cell states. In order to model biochemical kinetics accurately, stochastic effects must be taken into account. Since stochastic simulations are computational very challenging and time consuming often approximate methods are applied. In this contribution we propose an efficient approach, which captures various sources of noise simultaneously. Our approach relies on the unscented transformation to model uncertain parameters and the tau-leaping algorithm accounting for the inherent stochastic process of biochemical reactions.