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. Shastic methods are increasingly important, because shastic models are closer to the Brownian reality of the cellular and sub-cellular world.
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. Shastic methods are increasingly important, because shastic models are closer to the Brownian reality of the cellular and sub-cellular world.
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