Synopsis
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.
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Mathematical immunology is in a period of rapid expansion and excitement. At recent meetings, a common language and research direction has emerged amongst a world-class group of scientists and mathematicians. Mathematical Models and Immune Cell Biology aims to communicate these new ideas to a wider audience. The reader will be exposed to a variety of tools and methods that go hand-in-hand with the immunological processes being modeled. This volume contains chapters, written by immunologists and mathematicians, on thymocytes, on T cell interactions, activation, proliferation and homeostasis, as well as on dendritic cells, B cells and germinal centers. Chapters are devoted to measurement and imaging methods and to HIV and viral infections.
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