A Model of Immune Suppression and Repertoire Evolution
We present a stochastic cellular automata model that allows us to study both localized and generalized aspects of the immune system (IS). We show how critical values for T Cell Receptor (TCR) affinity and cross-reactivity (ρ) can determine the course of a viral infection. The model presented here offers insight into the widely varying pathology of infectious agents across individuals. Additionally, our model points to ways in which auto-immune disease can occur. We show that by integrating models of physical space and shape space we can analyze immune repertoire evolution and distribution over various time periods ranging from a few days up to three years.
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