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Y. G. Mei, R. Hontecillas, X. Y. Zhang, K. Bisset, S. Eubank, S. Hoops, M. Marathe and J. Bassaganya-Riera, “ENISI Visual, an Agent-Based Simulator for Modeling Gut Immunity,” IEEE International Conference on Bioinformatics and Biomedicine, Philadelphia, 4-7 October 2012, pp. 1-5.

has been cited by the following article:

• TITLE: Agent-Based Model: A Surging Tool to Simulate Infectious Diseases in the Immune System

  AUTHORS: Zhen Z. Shi, Chih-Hang Wu, David Ben-Arieh

  KEYWORDS: Agent-Based Model; Complex Biological Processes; Progression of Infectious Disease

  JOURNAL NAME: Open Journal of Modelling and Simulation, Vol.2 No.1, January 24, 2014

  ABSTRACT: Agent-based models (ABMs) are capable of constructing individual system components at different levels of representation to describe non-linear relationships between those components. Compared to a traditional mathematical modeling approach, agent-based models have an inherent spatial component with which they can easily describe local interactions and environmental heterogeneity. Furthermore, agent-based model maps interactions among agents inherently to the biological phenomenon by embedding the stochastic nature and dynamics transitions, thereby demonstrating suitability for the development of complex biological processes. Recently, an abundance of literature has presented application of agent-based modeling in the biological system. This review focuses on application of agent-based modeling to progression in simulation of infectious disease in the human immune system and discusses advantages and disadvantages of agent-based modeling application. Finally, potential implementation of agent-based modeling in relation to infectious disease modeling in future research is explored.