Overview
The advent of genomic technologies is leading to the generation of a vast amount of data detailing lists of cellular components, their functions and behaviour. As a result it is now becoming possible to interpret the behaviour of molecular processes within the context of a system of interacting components. Key to these studies are computer simulations which attempt to predict the behaviour of such systems.

Previous approaches have tended to use systems of partial or differential equations to represent various processes within a system (e.g. substrate turnover). However, whilst such models are useful in deriving insights into the kinetics of the system, they do not allow explorations into spatial properties associated with cellular systems preventing 3D visualisation which could otherwise also provide further insights into these molecular processes.

We are currently investigating simulation methods which are capable of accurately predicting the behaviour of complex molecular and cellular systems such as signaling, transport and metabolic processes. The specific aims are:

1. Develop a robust lattice modelling environment which can represent several different scales of the cell interior. Below is shown our latest attempts at constructing such an environment - Cell++. Cell++ is written in C++ and utilises the openGL and GLow graphics libraries. Buttons on the side of the window allow the user to interact with the simulation as it progresses.

2. Perform a series of experiments exploring key features thought to be important in signalling and metabolic processes including component concentration, spatial distribution, influence of cell architecture, potential of forming complexes and alternative schemes of network interaction. These experiments will have both hypothetical (exploring the boundaries of signalling / metabolic behaviour) and practical applications (modelling real systems which may uncover processes responsible for health and disease states).

3. Package the tool as a 3D interaction environment to allow researchers to gain non-intuitive insights into their system of interest.

Simulations can be viewed as they are being computed. The software is efficient enough to allow thousands of simulations to be performed on a single workstation overnight. This allows statistical analyses to be performed which are especially important given the stochastic nature of these pathways.