This article builds a sort of immune system model basing on cellular automata method, in order to simulate the immune response to tumor growth. This paper discusses immune-tumor system at the cellular level, based on the simple two-dimensional stochastic discrete cellular automaton model. In this simple three-layer structure designers take into account the features of the immune response, and regard many different kinds of immune cells as the single immune element. The model describes the interaction between cancer and immune cells, and shows immune cells growth around tumor. The authors study the normal cellular automaton model, and design the evolution growth rules. At last we build discrete cellular automaton model of tumor-immune system, and simulate tumor-immune system on computer. The model predicts the dynamics of the tumor-immune system in agreement with Gompertz growth. Via adjusting different parameters of simulating model, the ultimate results indicate the basal behaviors of tumor-immune system exactly.
[1]
Agostinho C. Rosa,et al.
Immune System Simulation through a Complex Adaptive System Model
,
2002
.
[2]
P. Morel,et al.
Mathematical modeling of immunological reactions.
,
1998,
Frontiers in bioscience : a journal and virtual library.
[3]
R Hofmann-Wellenhof,et al.
Cellular invasion without cellular motility in a stochastic growth model.
,
1996,
Analytical cellular pathology : the journal of the European Society for Analytical Cellular Pathology.
[4]
Stephen Wolfram,et al.
Cellular automata as models of complexity
,
1984,
Nature.
[5]
S Torquato,et al.
Simulated brain tumor growth dynamics using a three-dimensional cellular automaton.
,
2000,
Journal of theoretical biology.
[6]
X. Zheng,et al.
A cellular automaton model of cancerous growth.
,
1993,
Journal of theoretical biology.