A stochastic particle-based biological system simulator

The simulation and visualization of biological systems is expected to enhance our understanding of biological processes towards the development of effective therapeutic treatments. Biological systems are inherently stochastic at the molecular level, exhibit modified behavior under crowded conditions and may be affected by spatial locality. Common simulation approaches fail to account for these important aspects of biological systems, in part because they are computationally expensive. Here, we describe a stochastic, particle-based simulator that takes spatial locality into account. Each particle in the system is represented explicitly on a 3D grid where only one particle can occupy a grid location. The grid structure and stochastic approach removes the need for distance calculation and particle search. We demonstrate the effect of molecular crowding and spatial locality for a simple biological system. We anticipate that this system will be useful in examining more complex systems. Finally, this system is expected to be suitable for acceleration with parallel customizable hardware, a necessary requirement towards the simulation of an entire cell.