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Theory and Tools for Complex Biological Systems

复杂生物系统的理论和工具

基本信息

批准号：
EP/E049370/1
负责人：
Desmond Higham
金额：
$ 40.54万
依托单位：
University of Strathclyde
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2007
资助国家：
英国
起止时间：
2007 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FE049370%2F1
关键词：
Theory Tools Complex Biological Systems

项目摘要

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.

在现实生活中有很多情况下，连接模式很重要。例如，为了理解一种疾病如何在人群中传播，一种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“连接”有所了解。通过研究许多现实生活网络的典型模式，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，科学家们发现了一些似乎普遍存在的共同特征。此外，他们还提出了一些规则，似乎可以支配现实生活中网络的发展。通常，有必要总结这样一个极其复杂的信息集，可能是通过寻找行为相似的对象集群，或者通过以自然的方式对对象进行排序，以便相邻的对象具有相似的特征。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接模式。为了给这项工作一个坚实的基础，所有的想法都将在有关基因和蛋白质在细胞中的行为的真实的、前沿的数据上进行测试。该项目的这方面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比特森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，任何新的发现都可能对医疗保健和药物设计有直接的好处。

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Evolving graphs: dynamical models, inverse problems and propagation

DOI：
10.1098/rspa.2009.0456
发表时间：
2010-03-08
期刊：
PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
影响因子：
3.5
作者：
Grindrod, Peter;Higham, Desmond J.
通讯作者：
Higham, Desmond J.

Geometric de-noising of protein-protein interaction networks.