Mathematics of Biological Systems: Modelling, Data & Analysis

要预测和预防癌症、糖尿病和艾滋病等疾病，我们需要做的不仅仅是确定构成细胞和组织机械的组件。我们还必须了解这些组成部分如何相互作用，以产生正常和病理性的行为。由于基因、转录物、蛋白质、代谢物和细胞之间的相互作用是复杂的和动态的，需要数学建模和分析才能理解它们。此外，有许多快速增长的强大技术来探测基因表达以及代谢物和蛋白质的丰度和空间分布。这些产生了大量的数据，需要开发新的数学和统计方法。这一问题和相关的实验设计问题提出了相当大的数学和统计学挑战。这项工作将在一些生物学领域进行，期望这些领域获得的结果可能是可推广的。这些包括生物钟、光周期、T细胞的免疫学、植物发育(开花)、细胞凋亡的控制(细胞自杀)和复制，以及细菌信号。这项研究涉及与实验小组的广泛合作，并将在数学和物理科学家以及生物学家和临床医生参与的多学科背景下进行。

To predict and preventing diseases such as cancer, diabetes and AIDS we need to do more than identify the components that make up the machinery of cells and tissues. We must also understand how these components interact to produce normal and pathological behaviour. Since the interactions between genes, transcripts, proteins, metabolites and cells are complex and dynamics, mathematical modelling and analysis will be needed for their understanding. Moreover, there is a rapidly growing number of powerful technologies that probe gene expression and the abundance and spatial distribution of metabolites and proteins. These produce huge amounts of data and require the development of new mathematical and statistical methods. This and the associated experimental design problems pose considerable mathematical and statistical challenges.This work will be developed in a number of biological areas chosen with the expectation that results obtained for these are likely to be generalisable. These include circadian clocks, photoperiodism, immunology of T cells, plant development (flowering), the control of apoptosis (cell suicide) and replication, and bacterial signalling. The research involves extensive collaboration with experimental groups and will be carried out in a multidisciplinary context involving mathematical and physical scientists as well as biologists and clinicians.