Bio-QuBIC: Causes of Robustness and Vulnerability in Real-world Networks: Lessons from Molecular Biology

Bio-QuBIC：现实世界网络鲁棒性和脆弱性的原因：分子生物学的教训

• 批准号: 0130059
• 负责人: Animesh Ray
• 金额: $ 50.11万
• 依托单位: Keck Graduate Institute
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-15 至 2004-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0130059&HistoricalAwards=false
• 关键词: Bio; QuBIC; Causes; Robustness; Vulnerability

EIA-0130059Animesh RayKeck Graduate InstituteTitle: Causes of Robustness and Vulnerability in Real-world Networks: Lessons from molecular biologyVulnerability of natural networks (such as the Internet, power supply grid, or molecular regulatory circuits of cells) to perturbations is an important area of study. Prior work has traditionally involved observations on static networks or on computer simulations, and has revealed certain general fundamental properties. Specifically, the study of one representative natural network by direct experimental manipulation should illuminate general properties of most networks. The molecular machinery regulating the synthesis of RNA molecules in the nucleus of budding yeast forms a natural network that can be experimentally perturbed, and their effects studied by transcriptional profiling on DNA microarrays. In this initial funding period, study of the responses of a sub-section (comprised of approximately 300 nodes) of this natural network as a function of precise perturbations in the form of gene knockout mutations. A queriable, static, database model of the network is being made, which is queried by simple attack plans, and responses are tested for consistency with experimental results. This interplay is allowing a proof-of-principle demonstration of this empirical approach to studying properties of complex networks. Insights obtained from these studies is forming the basis of more sophisticated investigation of complex network properties.

EIA-0130059Animesh RayKeck 研究生院标题：现实世界网络中鲁棒性和脆弱性的原因：分子生物学的教训自然网络（例如互联网、供电网或细胞的分子调节电路）对扰动的脆弱性是一个重要的研究领域。 先前的工作传统上涉及对静态网络或计算机模拟的观察，并揭示了某些一般的基本属性。 具体来说，通过直接实验操作对一个代表性自然网络的研究应该能够阐明大多数网络的一般特性。 芽殖酵母细胞核中调节 RNA 分子合成的分子机制形成了一个可以通过实验扰动的自然网络，并通过 DNA 微阵列的转录分析来研究它们的影响。 在最初的资助期间，研究了该自然网络的一个子部分（由大约 300 个节点组成）的响应，作为基因敲除突变形式的精确扰动的函数。正在建立一个可查询的、静态的网络数据库模型，通过简单的攻击计划来查询该模型，并测试响应与实验结果的一致性。 这种相互作用允许对这种研究复杂网络特性的经验方法进行原理验证演示。 从这些研究中获得的见解正在构成对复杂网络属性进行更复杂研究的基础。