Stochastic models of T cell receptor and cytokine receptor signalling: a mathematical and computational approach

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This project supports the Healthcare Technologies Theme by providing cost-effective computational tools to aid development and optimisation of treatments for intracellular bacterial infections using Francisella tularensis as a case study.Mathematical models and statistical models will be developed to enable simulation of the within-host mechanisms of infection and immune response allowing potential interventions to be explored in silico. A wide range of biological and immunological data will be integrated to increase understanding of the mechanisms at molecular, cellular and population levels.This application intersects the EPSRC research areas od biological informatics, complexity science and non-linear systems, employing mathematical, statistical and numerical techniques. The work will provide novel computational tools for operational research which will be utilised by the Project Partner.