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

该项目支持医疗保健技术主题，提供具有成本效益的计算工具，帮助开发和优化细胞内细菌感染的治疗方法，以图拉氏方济氏菌为例。将开发数学模型和统计模型，以模拟宿主内感染和免疫反应的机制，从而探索在硅胶中可能的干预措施。广泛的生物学和免疫学数据将被整合，以增加对分子、细胞和种群水平的机制的理解。这一应用交叉于EPSRC的生物信息学、复杂性科学和非线性系统的研究领域，利用数学、统计和数值技术。这项工作将为运筹学提供新的计算工具，供项目伙伴使用。

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.