TY - JOUR
T1 - Hybrid Simulation Algorithms for an Agent Based Model of the Immune Response
AU - Textor, Johannes
AU - Hansen, Björn
PY - 2009
Y1 - 2009
N2 - The immune system is of central interest for the life sciences, but its high complexity makes it a challenging system to study. Computational models of the immune system can help to improve our understanding of its fundamental principles. In this article, we analyze and extend the Celada-Seiden model, a simple and elegant agent-based model of the entire immune response, which, however, lacks biophysically sound simulation methodology. We extend the stochastic model to a stochastic-deterministic hybrid, and link the deterministic version to continuous physical and chemical laws. This gives precise meaning to all simulation processes, and helps to increase performance. To demonstrate an application for the model, we implement and study two different hypotheses about T cell-mediated immune memory.
AB - The immune system is of central interest for the life sciences, but its high complexity makes it a challenging system to study. Computational models of the immune system can help to improve our understanding of its fundamental principles. In this article, we analyze and extend the Celada-Seiden model, a simple and elegant agent-based model of the entire immune response, which, however, lacks biophysically sound simulation methodology. We extend the stochastic model to a stochastic-deterministic hybrid, and link the deterministic version to continuous physical and chemical laws. This gives precise meaning to all simulation processes, and helps to increase performance. To demonstrate an application for the model, we implement and study two different hypotheses about T cell-mediated immune memory.
UR - https://www.tandfonline.com/doi/full/10.1080/01969720902922384
M3 - Journal articles
SP - 390
EP - 417
JO - Cybernetics and Systems
JF - Cybernetics and Systems
ER -
