Whole new areas of immunological research are emerging from the analysis of experimental data, going beyond statistics and parameter estimation into what an applied mathematician would recognise as modelling of dynamical systems. Stochastic methods are increasingly important, because stochastic models are closer to the Brownian reality of the cellular and sub-cellular world.
Contains chapters on mathematical modelling, on immunology, and on mathematical modelling in immunology
Reader will also find chapters on dendritic cells, B cells and germinal centers
Contains a list of abbreviations to help indicate the type of research that is being carried out