Accommodating space, time and randomness in network simulation

Abstract

Interest in the possibility of dynamically simulating complex cellular processes has escalated markedly in recent years. This interest has been fuelled by three factors: the generally accepted value in understanding living processes as integrated systems; the dramatic increase in computational capability; and the availability of new or improved technology for making the quantitative measurements that are needed to drive and validate cellular simulations. Between the extremes of atom-scale and organism-scale simulation is a vast middle-ground requiring simulation strategies that are capable of dealing with a range of spatial, temporal and molecular abundance scales that are crucial for a comprehensive understanding of integrative cell biology. Although at an early stage, methodological improvements and the development of computational platforms provide some hope that simulations will emerge that can bridge the gap between network models and the true operation of the cell as a complex machine.