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Computational Challenges in Biochemical Networks: Multiscale Modelling and Inverse Problems

生化网络中的计算挑战：多尺度建模和反问题

基本信息

批准号：
EP/L023393/1
负责人：
Simon Cotter
金额：
$ 11.98万
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2014
资助国家：
英国
起止时间：
2014 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FL023393%2F1
关键词：
Computational Challenges Biochemical Networks Multiscale

项目摘要

In the last 20 years, technologies have been developed which allow biologists to observe, in real time, the reactions which are occurring in a single cell. These new developments have the potential to give us a whole new understanding of how cells function. In particular, it gives us a tool with which we can make great leaps in our understanding of how our genes operate and affect the way cells behave, multiply, and die. The understanding of these mechanisms is key in developing treatments for conditions for when they go wrong, for instance in cancer. As such, this relatively young area of science could be very important for the future of the health of humankind.The use of these technologies is increasing rapidly amongst biologists, but the problem remains as how best to interpret this data, and allow us to understand what we have observed. What is more, the observational methods are far from perfect, and are full of small errors which could cloud our conclusions. Therefore it is important that we understand the underlying mathematics within these problems, in a bid to extract as much reliable information from this data as possible. The aim of this project is to study the mathematical theory behind, and develop new computer algorithms for, the analysis of this type of data. The Bayesian philosophy is a mathematical framework which allows us to not only identify likely biochemical mechanisms which could have caused the phenomena we observe in the experiments, but also to quantify how much we should believe our own results. This project will have significant impact on this area, and help to cement the UK's position as one of the leading places to conduct biological and pharmaceutical research, which plays such an important part in our economy. Furthermore, it will enhance the UK's reputation for high quality interdisciplinary applied mathematics research.

在过去的20年里，已经开发了一些技术，使生物学家能够实时观察在单个细胞中发生的反应。这些新的发展有可能让我们对细胞的功能有一个全新的理解。特别是，它为我们提供了一种工具，使我们能够在理解我们的基因如何运作以及影响细胞的行为、繁殖和死亡方式方面取得巨大飞跃。对这些机制的理解对于开发针对疾病的治疗方法至关重要，例如在癌症中。因此，这个相对年轻的科学领域对人类健康的未来可能非常重要。这些技术在生物学家中的使用正在迅速增加，但问题仍然是如何最好地解释这些数据，并允许我们理解我们观察到的东西。更重要的是，观测方法远非完美，而且充满了可能会模糊我们结论的小误差。因此，重要的是我们要理解这些问题背后的数学原理，以便从这些数据中提取尽可能多的可靠信息。这个项目的目的是研究这类数据分析背后的数学理论，并开发新的计算机算法。贝叶斯哲学是一个数学框架，它不仅允许我们识别可能导致我们在实验中观察到的现象的生化机制，而且还可以量化我们应该在多大程度上相信我们自己的结果。该项目将对这一领域产生重大影响，并有助于巩固英国作为开展生物和药物研究的领先地区之一的地位，生物和药物研究在我们的经济中发挥着如此重要的作用。此外，它还将提高英国在高质量跨学科应用数学研究方面的声誉。