Theory and Tools for Complex Biological Systems

在真实的生活中，有许多情况下，人际关系的模式是很重要的。例如，要了解疾病如何在人群中传播，病毒如何在计算机网络中传播，或者信号如何在大脑中传递，我们必须对组件之间的“布线”有所了解。通过研究许多真实的生活网络中的典型模式，包括大脑神经元、计算机、网页、人、合著者和电话用户之间的连接数据，科学家们发现了似乎具有普遍性的共同特征。此外，他们还提出了一些规则，这些规则似乎可以支配真实的生活网络的发展。通常情况下，有必要总结这样一个极其复杂的信息集，也许是通过寻找行为相似的物体群，或者通过自然方式对物体进行排序，以便邻居具有相似的特征。该项目将开发新的计算工具，用于组织大型数据集和解释观察到的连通性模式。为了给这项工作一个坚实的基础，所有的想法都将在关于细胞中基因和蛋白质行为的真实的前沿数据上进行测试。这方面的项目工作将与来自生命科学的同事密切合作，特别是来自格拉斯哥的Beatson研究所的癌症研究人员。这些同事将帮助我们提出正确的问题。此外，在我们设计了新的计算算法之后，这些同事也将帮助我们解释答案。在这一重要的生物学应用中的任何新发现都可能对医疗保健和药物设计产生直接的好处。

There are many circumstances in real life where patterns of connecitivityare important. For example, to understand how a disease may spread around a population,how a virus may spread around a computer network or how signals are passed around the brain, wemust have some idea of the `wiring' between components. By studying the typicalpatterns in many real life networks, including data concerning connectivity between brain neurons, computers, web pages, people, co-authors and telephone users, scientistshave discovered common features that seem to be universal. Also, they have come upwith rules that appear to govern the development of real life networks. Often, it is necessary to summarize such an enormously complex set of information, perhaps byfinding clusters of objects that behave similarly or by ordering the objects in a natrual manner,so that neighbours have similar features.This project will develop new computational tools for organizing large data sets and for explaining the patterens of connectivity that are observed. To give the work a firm grounding, all ideas will be tested on real, cutting-edge data concerning the behaviour of genes and proteinsin the cell. This aspect of the project work will be done in close collaboration with colleagues from the life sciences, notably cancer researchers from the Beatson Institute in Glasgow. These colleagues will help us to formulate the right questions. Further, after we have designed the new computational algorithms, these colleagues will also help us to interpret the answers. Any new findings in this important biological application could have direct benfits to healthcare and drug design.