Chiacchio Ferdinando, Pennisi Marzio, Russo Giulia, Motta Santo, Pappalardo Francesco
Department of Electric, Electronics and Computer Engineering, University of Catania, V.le A. Doria 6, 95125 Catania, Italy.
Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125 Catania, Italy.
Biomed Res Int. 2014;2014:907171. doi: 10.1155/2014/907171. Epub 2014 Apr 22.
Several components that interact with each other to evolve a complex, and, in some cases, unexpected behavior, represents one of the main and fascinating features of the mammalian immune system. Agent-based modeling and cellular automata belong to a class of discrete mathematical approaches in which entities (agents) sense local information and undertake actions over time according to predefined rules. The strength of this approach is characterized by the appearance of a global behavior that emerges from interactions among agents. This behavior is unpredictable, as it does not follow linear rules. There are a lot of works that investigates the immune system with agent-based modeling and cellular automata. They have shown the ability to see clearly and intuitively into the nature of immunological processes. NetLogo is a multiagent programming language and modeling environment for simulating complex phenomena. It is designed for both research and education and is used across a wide range of disciplines and education levels. In this paper, we summarize NetLogo applications to immunology and, particularly, how this framework can help in the development and formulation of hypotheses that might drive further experimental investigations of disease mechanisms.
几个相互作用以产生复杂且在某些情况下意想不到的行为的组件，代表了哺乳动物免疫系统的主要迷人特征之一。基于主体的建模和细胞自动机属于一类离散数学方法，其中实体（主体）感知局部信息并根据预定义规则随时间采取行动。这种方法的优势在于出现了一种源于主体间相互作用的全局行为。这种行为是不可预测的，因为它不遵循线性规则。有许多工作使用基于主体的建模和细胞自动机来研究免疫系统。它们已显示出能够清晰直观地洞察免疫过程的本质。NetLogo是一种用于模拟复杂现象的多主体编程语言和建模环境。它专为研究和教育设计，广泛应用于各种学科和教育水平。在本文中，我们总结了NetLogo在免疫学中的应用，特别是这个框架如何有助于提出可能推动对疾病机制进行进一步实验研究的假设并进行阐述。
