BIC: From Cellular and Gene Networks To Principles of Robust Communication and Distributed Systems Design

BIC：从细胞和基因网络到鲁棒通信和分布式系统设计的原理

• 批准号: 0524843
• 负责人: Vwani Roychowdhury
• 金额: $ 50万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-15 至 2010-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0524843&HistoricalAwards=false
• 关键词: BIC; Cellular; Gene; Networks; Principles

An interdisciplinary approach involving concepts from computer science, mathematics, statistical physics, and communication sciences, is proposed to develop an integrated analytical and software platform that would simultaneously facilitate the analysis and understanding of several types of biological and social networks, including DNA-protein, protein-protein, metabolic, and inter-cellular signaling networks, and the design of information and computational networks, including fault-tolerant and attack-resistant federated databases and ad hoc communication networks, and distributed systems such as critical infrastructure networks (e.g., national power grids). The field of complex networks has evolved in a highly synergistic fashion, involving the physical and life sciences, computing and engineering disciplines. This proposal aims to develop a common set of tools for the diverse communities, thus promoting cross-pollination of ideas, and spurring the development of integrated technologies and innovations. In the past, most work on complex networks has been analysis-oriented; that is, identifying and measuring different characteristics of existing systems (e.g., the Internet, protein-protein interactions, empirical social networks) and proposing potential dynamics that could have led to the emergence of such systems. This proposal, focuses on a more balanced approach, where in addition to the modeling work, it also addresses the issue of how the modeling work can be harnessed to design information networks, and how to formulate systematic methods for mining the information available from complex networks. Specific topics and issues pursued include: (1) Network Tomography - Inferring hidden structures from observed data: What are the structural characteristics of biological networks and how have they evolved and formed? The recent flood of data concerning large-scale biological networks are just beginning to be analyzed, and the PI proposes to design a set of complex network tools to address these issues. (2) Information Dynamics In Complex Networks: How is information processed and communicated in complex networks? Can synchronization or stable communication among nodes arise in networks where the connectivity is itself time varying and the same pair of nodes are only intermittently connected? (3) Net-Modeler: development of a comprehensive complex network modeler to be used for both static and dynamical explorations of biological networks; (4) Designer Complex Systems - Designing Dynamic Information and Computing Networks: How to harness the structure and functionalities of the biological and other complex networks to design local protocols of a distributed and ad hoc networked system, so that the system has the desired global properties, such as low-latency and robust functionality? The methodologies and software tools developed in the proposal will be integrated into a virtual web-based laboratory. This will lead to (i) a nationwide resource for the analysis of biological and social networks, and (ii) interdisciplinary undergraduate and graduate courses and training programs on complex networks and their applications.

An interdisciplinary approach involving concepts from computer science, mathematics, statistical physics, and communication sciences, is proposed to develop an integrated analytical and software platform that would simultaneously facilitate the analysis and understanding of several types of biological and social networks, including DNA-protein, protein-protein, metabolic, and inter-cellular signaling networks, and the design of information and computational networks, including fault-tolerant and attack-resistant联合数据库和临时通信网络以及分布式系统，例如关键基础架构网络（例如，国家电力网格）。复杂网络的领域已经以高度协同的方式发展，涉及物理和生活科学，计算和工程学科。该建议旨在为各种社区开发一套通用工具，从而促进思想的交叉授粉，并促进综合技术和创新的发展。过去，大多数在复杂网络上的工作都以分析为导向。也就是说，识别和测量现有系统的不同特征（例如，互联网，蛋白质 - 蛋白质相互作用，经验社交网络），并提出可能导致这种系统出现的潜在动态。该提案重点介绍了一种更加平衡的方法，除了建模工作外，它还解决了如何利用建模工作来设计信息网络的问题，以及如何制定系统的方法来挖掘复杂网络可用的信息。所追求的特定主题和问题包括：（1）网络层析成像 - 从观察到的数据中推断出隐藏的结构：生物网络的结构特征是什么？它们如何发展和形成？关于大规模生物网络的最新数据泛滥开始刚刚开始分析，PI建议设计一组复杂的网络工具来解决这些问题。 （2）复杂网络中的信息动态：如何在复杂网络中处理和传达信息？节点之间的同步或稳定的通信能否在连接本身变化而相同的节点的网络中出现同步或稳定的通信？ （3）Net Modeler：开发全面的复杂网络建模器，用于生物网络的静态和动态探索； （4）设计师复杂系统 - 设计动态信息和计算网络：如何利用生物学和其他复杂网络的结构和功能来设计分布式和临时网络系统的本地协议，以便该系统具有所需的全球属性，例如低规模和鲁棒功能？该提案中开发的方法和软件工具将集成到基于虚拟的基于Web的实验室中。这将导致（i）用于分析生物和社交网络的全国资源，以及（ii）有关复杂网络及其应用的跨学科本科和研究生课程以及培训计划。