Network models of T cell receptor repertoires, cross-reactivity, and viral infection

The mathematical models of this Thesis represent T cell population dynamics in homeostasis and during infection. In particular, T cell cross-reactivity is studied with a bipartite recognition network encoding the epitope recognition profiles of T cell receptors. The behaviour of extinction events is studied using stochastic models. Stochastic and deterministic techniques are used to study the late time behaviour of the system. Statistical methods are used to study immune responses in the context of influenza A virus infection in mice, providing insight into the effects of immunological history and cross-reactivity. Finally, network theoretical tools are used to study the dynamics of cross-reactive immune responses under different hypotheses for the structure of the bipartite recognition network.