Collaborative Research: ABI Innovation: BCSP: Understanding the design and usage of distributed biological networks

合作研究：ABI 创新：BCSP：了解分布式生物网络的设计和使用

• 批准号: 1356505
• 负责人: Ziv Bar-Joseph
• 金额: $ 84.78万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1356505&HistoricalAwards=false
• 关键词: Collaborative; Research; ABI; Innovation; BCSP

Computer science and biology have enjoyed a long and fruitful relationship for decades. Biologists rely on computational methods to analyze and integrate large data sets, while several computational methods were inspired by the high-level design principles of biological systems. Several common aspects and goals of computational and biological systems suggest that we can use one as a source for studies of the other and vice versa. With recent advances in our ability to generate and analyze biological data it is now possible, for the first time, to design new, bi-directional studies that directly link biology and computer science. This form of coupled experimental and computational thinking, which will be utilized in this project, can greatly benefit both biology and computer science. The proposal also seeks to help establish the usefulness of this approach to increase public interest in science and engineering and to provide interdisciplinary educational and research experiences for a diverse population of students.This joint experimental-computational project will use a bi-directional approach to study the design, communication and coordination of networks utilized by Escherichia coli. The overall goal is to determine how biological systems utilize distributed networks over different scales, environments and varying communication strategies. The project will address biological questions ranging from how information processing is performed in signaling networks to the importance of various topological features of E. coli networks to coordination in a population of bacterial cells. In addition to addressing the biological questions these studies seek to provide insights into the design and usage of networks for distributed computational systems that can tolerate harsh environments, failures and limited resources making them applicable to a wide range of real world applications. Distributed networks are utilized by species ranging from single cell organisms to mammals. The proposal seeks to determine shared principles regarding the design and usage of such networks in E. coli. and the findings can be applied to understand similar systems in other species, as well. Beyond the immediate impact of the biological modeling and the algorithms developed, the synergy between computational and biological systems is of great interest to computer scientists, biologists and the general public. The proposal includes an interdisciplinary collaboration between computer scientists, engineers and biologists. Students funded as part of this project will spend time at collaborators' labs from other disciplines leading to interdisciplinary training and the research will support and provide training opportunities for undergraduate and graduate students from underrepresented groups. The PI and co-PIs plan to develop and offer a new class on biologically inspired computational methods and to organize workshops and tutorials in relevant international meetings about the topic of this proposal. Project outcomes will be disseminated at http://www.algorithmsinnature.org.

数十年来，计算机科学和生物学一直在悠久而富有成果的关系。生物学家依靠计算方法来分析和整合大型数据集，而几种计算方法的灵感来自生物系统的高级设计原理。计算和生物系统的几个常见方面和目标表明，我们可以将一个方面作为对另一个研究的来源，反之亦然。随着我们生成和分析生物学数据能力的最新进展，现在首次设计了直接联系生物学和计算机科学的新的双向研究。这种项目将在该项目中使用的这种耦合实验和计算思维形式可以极大地使生物学和计算机科学受益。该提案还旨在帮助建立这种方法的实用性，以提高公众对科学和工程的兴趣，并为多样化的学生提供跨学科的教育和研究经验。这项联合实验性计算项目将使用双向研究方法来研究由Escherichia Coli使用的网络设计，交流和协调。总体目标是确定生物系统如何利用不同尺度，环境和不同沟通策略的分布式网络。该项目将解决从信号网络中如何进行信息处理到大肠杆菌网络各种拓扑特征到细菌细胞种群协调的重要性的生物学问题。除了解决生物学问题外，这些研究试图为分布式计算系统的网络设计和使用提供见解，这些计算系统可以容忍恶劣的环境，失败和有限的资源，从而使其适用于广泛的现实世界应用。分布式网络是通过从单细胞生物到哺乳动物的物种来利用的。该提案旨在确定有关此类网络在大肠杆菌中的设计和使用的共同原则。这些发现也可以用于了解其他物种中的类似系统。除了生物建模和开发算法的直接影响外，计算和生物系统之间的协同作用对计算机科学家，生物学家和公众引起了极大的兴趣。 该提案包括计算机科学家，工程师和生物学家之间的跨学科合作。作为该项目的一部分资助的学生将在其他学科的合作者实验室中度过一段时间，该学科进行跨学科培训，研究将为来自代表性不足的小组的本科生和研究生提供支持并为培训机会。 PI和CO-PIS计划在有关该提案主题的相关国际会议上开发和提供有关生物学启发的计​​算方法的新课程，并组织研讨会和教程。 项目成果将在http://www.algorithmsinnature.org上传播。