Towards dynamic simulation of a whole cell model

Whole-cell models (WCMs) aim to integrate the sum of our knowledge about the mechanistic processes of an organism that are inherently multi-scale and dynamic. Such comprehensive models would enable us to address many challenging questions, such as understanding interactions and coupling between pathways, examining system properties, and identifying gaps in our biological knowledge. WCMs integrate a diverse array of intracellular pathways through an equally diverse assortment of computational methods. Among these methods, stochastic simulation helps implement the most detailed model. However, it is also the most time consuming to execute. Furthermore, WCMs involve some of the largest known biochemical reaction networks. To speed up the simulation and accelerate the development of such a model, we present a parallel implementation of stochastic simulation algorithm (SSA) and its application to a whole cell reaction network.