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BioMed Research International
Volume 2014, Article ID 907171, 6 pages
http://dx.doi.org/10.1155/2014/907171
Review Article

Agent-Based Modeling of the Immune System: NetLogo, a Promising Framework

1Department of Electric, Electronics and Computer Engineering, University of Catania, V.le A. Doria 6, 95125 Catania, Italy
2Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125 Catania, Italy
3Department of Drug Sciences, University of Catania, V.le A. Doria 6, 95125 Catania, Italy

Received 27 January 2014; Accepted 2 April 2014; Published 22 April 2014

Academic Editor: Filippo Castiglione

Copyright © 2014 Ferdinando Chiacchio et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

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.