Synonyms
Cellular automata (or automaton); Individual-based models
Acronyms
- ABM::
-
Agent-based model
- Abs::
-
Antibodies
- CTL::
-
Cytotoxic T lymphocyte
- IR::
-
Immune response
- NK::
-
Natural killer cells
- ODE::
-
Ordinary differential equation
- Th::
-
Helper T cell
Short Definition
Agent-based models (or ABMs) of infectious diseases and/or immunological systems are computer models for which the key units of the modeled system – pathogens, target cells, immune cells – are explicitly represented as discrete, autonomous agents characterized by a set of states (e.g., infected, activated). Transition of an agent between states or its movement through space (if applicable) obeys a set of rules based on the agent’s current internal states (e.g., if the cell has been alive for 3 h then it transitions to the dead state), that of its neighbors (e.g., if the cell’s neighbor is infected, then it has a 20 % chance of transitioning to the infected state), and/or its perception of its external environment (e.g., if...
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References
Bauer, A.L., Beauchemin, C.A., Perelson, A.S.: Agent-based modeling of host-pathogen systems: the successes and challenges. Info. Sci. 179(10), 1379–1389 (2009). doi:10.1016/j.ins.2008.11.012
Beauchemin, C., Forrest, S., Koster, F.T.: Modeling influenza viral dynamics in tissue. In: Bersini, H., Carneiro, J. (eds.) Proceedings of the 5th International Conference on Artificial Immune Systems (ICARIS 06), Lecture Notes in Computer Science, vol. 4163, pp. 23–36. Springer, Berlin Heidelberg (2006). doi:10.1007/11823940_3
Chavali, A.K., Gianchandani, E.P., Tung, K.S., Lawrence, M.B., Peirce, S.M., Papin, J.A.: Characterizing emergent properties of immunological systems with multi-cellular rule-based computational modeling. Trends Immunol. 29(12), 589–599 (2008). doi:10.1016/j.it.2008.08.006
Forrest, S., Beauchemin, C.: Computer immunology. Immunol. Rev. 216(1), 176–197 (2007). doi:10.1111/j.1600-065X.2007.00499.x
Kindt, T.J., Goldsby, R.A., Osborne, B.A., Kuby, J.: Kuby Immunology, 6th edn. W. H. Freeman and Company, New York (2007)
Louzoun, Y.: The evolution of mathematical immunology. Immunol. Rev. 216(1), 9–20 (2007). doi:10.1111/j.1600-065X.2006.00495.x;
Nowak, M.A., May, R.M.: Virus Dynamics: Mathematical Principles of Immunology and Virology. Oxford University Press, Oxford (2000)
Seiden, P.E., Celada, F.: A model for simulating cognate recognition and response in the immune system. J. Theor. Biol. 158(3), 329–357 (1992). doi:10.1016/S0022-5193(05)80737-4
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Beauchemin, C.A.A. (2015). Agent-Based Models in Infectious Disease and Immunology. In: Engquist, B. (eds) Encyclopedia of Applied and Computational Mathematics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70529-1_38
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DOI: https://doi.org/10.1007/978-3-540-70529-1_38
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