Abstract

Recently, systems and synthetic biology rely more and more on mathematical modeling and computational simulation to predict the behavior of biological systems and facilitate the understanding of novel models. Due to time-consuming lab work and expense, modeling and simulation can help us to avoid wasting many materials, investigate functional properties.
As far as we all know, many models have focused on intracellular dynamics, which are describing how the concentration of the key chemicals, such as mRNA and proteins vary over time within only single cell. Though it may be very convenient for us to make sense of single cell, many behaviors occur at the population level eg., bacterial coordination, communication and cooperative growth and important during infection.
In order to know how the systems work，we should not only consider the intracellular behaviors, but the interactions between individual cells in population-level.
Cellular automation is a discrete model studied in computational biology, physics and microstructure modeling. As it can use agent-based or individual-based models to raise the models of low-level interactions to population level behaviors, cellular automation may be of wonderful use in simulating micro-models.