Revealing Structure via Dynamics: Biological Networks from Protein Folding to Food Webs

通过动力学揭示结构：从蛋白质折叠到食物网的生物网络

• 批准号: 1038677
• 负责人: Robin Snyder
• 金额: $ 66万
• 依托单位: Case Western Reserve University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1038677&HistoricalAwards=false
• 关键词: Revealing; Structure; via; Dynamics; Biological

A principal goal of biological theory is to understand complex living systems in terms of their parts and the interactions between their parts. In this project, an ecologist, a protein physiologist and a mathematician will collaborate to develop new ways of understanding how highly interconnected biological systems change through time. Specifically, these investigators aim to develop a general theory of linear dynamics on complex biological networks. Surprisingly, a great variety of critically important biological phenomena at a wide range of scales is captured by linear or approximately linear dynamics on complex networks. By applying novel methods for coarse graining biological networks, this project will answer questions such as: how many functionally distinct moving parts does a given system have? How do quantities of interest, such as nutrients or information, move through a highly interconnected network? Which nodes or edges in such a network are the most important for transmission? Can we identify nodes whose removal has the greatest or smallest effect on the performance of the network?Developing a framework for general linear dynamics on complex biological networks will have a broad and deep impact on our ability to understand, predict and control critically important biological processes at a wide range of scales. In addition, this project will contribute to training students at the undergraduate, graduate and postdoctoral level to work across disciplines such as ecology, physiology and mathematics to deepen our understanding of complex biological systems.

生物学理论的一个主要目标是理解复杂的生命系统，包括它们的组成部分以及它们之间的相互作用。 在这个项目中，一位生态学家、一位蛋白质生理学家和一位数学家将合作开发新的方法来理解高度相互关联的生物系统如何随着时间的推移而变化。 具体来说，这些研究人员的目标是发展一个线性动力学的复杂生物网络的一般理论。 令人惊讶的是，在广泛的尺度上，各种各样的至关重要的生物现象都被复杂网络上的线性或近似线性动力学所捕获。 通过应用新的方法来粗粒度生物网络，该项目将回答这样的问题：一个给定的系统有多少功能不同的运动部件？ 营养物或信息等感兴趣的量是如何在高度互联的网络中移动的？ 在这样的网络中，哪些节点或边对传输最重要？ 我们能否确定哪些节点的删除对网络性能的影响最大或最小？在复杂的生物网络上开发一个一般线性动力学的框架，将对我们在广泛的尺度上理解、预测和控制至关重要的生物过程的能力产生广泛而深刻的影响。 此外，该项目将有助于培养本科生，研究生和博士后水平的学生跨学科工作，如生态学，生理学和数学，以加深我们对复杂生物系统的理解。