Biological Computer Modeling / Biological Computer Simulation
Seyed Hojat Sabzpoushan; Fateme Pourhasanzade
Volume 11, Issue 1 , May 2017, , Pages 1-18
Abstract
In this paper, a new method is proposed for slowing down avascular tumor growth. Our method is established on an agent based avascular tumor growth model (ABM). The model is based on biological assumptions with regard to the immune system interactions. The model parameters are fitted in compatability ...
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In this paper, a new method is proposed for slowing down avascular tumor growth. Our method is established on an agent based avascular tumor growth model (ABM). The model is based on biological assumptions with regard to the immune system interactions. The model parameters are fitted in compatability with cancer biology using in vivo expremental data. The immune cells recruitment, which usually occur after that tumor cells are identified, are also considered in ABM model. The results show that the proposed model not only is able to simulate the tumor growth graphically, but also the in vivo tumor growth quantitatively and qualitatively. Besides, the model proposes a new idea for slowing down the tumor growth considering two types of prolaiferative tumor cells, i.e. the tumor will grow slowly if the division probability of the proliferative tumor cells depends on the microenvironmental conditions. The proposed idea has been validated using an in silico simulation.
Cell Biomechanics / Cell Mechanics / Mechanobiology
Siavash Mazdeyasna; Amir Homayoun Jafari
Volume 5, Issue 3 , June 2011, , Pages 181-192
Abstract
In this paper, two models are introduced based on cellular automata and the game theory to study behavior, growth, development and morphology of cancerous cells by assuming nutrition supplies, extracellular matrix, and immune cells. A two-dimensional cellular automaton combine with game theory is considered ...
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In this paper, two models are introduced based on cellular automata and the game theory to study behavior, growth, development and morphology of cancerous cells by assuming nutrition supplies, extracellular matrix, and immune cells. A two-dimensional cellular automaton combine with game theory is considered as the structure of model. The cellular automata modeling framework can be an efficient approach to a number of biological problems; and game theory aims to help us to understand situations in which decision-makers interact such as competitive activity. In the first model, we consider different oxygen supplies to study the growth and invasion of cancerous cell. The results of our simulation are validated by the results of other articles. The results show that the number of cancerous cells is easily changed by changing amount of oxygen supplies, but invasive distance of tumor cells is not easily affected by this factor. Furthermore the results of this model are not linear, that could show the improvement of the model. In addition, this model has the ability of producing metastasis, as it is shown. In the second model, the interaction between immune cells and cancerous cells are considered. Two-dimensional cellular automata and game theory are used for this purpose. In this model the behavior of cellular automata is determined by the game theory. The rules of cellular automata are determined by game theory table, so each element of the system could make a decision separately.