Mathematical Frameworks for Biological Modular Networks

生物模块化网络的数学框架

• 批准号: 0827508
• 负责人: Hernan Makse
• 金额: $ 52.33万
• 依托单位: CUNY City College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0827508&HistoricalAwards=false
• 关键词: Mathematical; Frameworks; Biological; Modular; Networks

The objective of this project is to understand evolutionary principles by which biological networks have acquired their modular architecture, robustness and preservation of diverse functions to sustain life. While much is known about the general rules of natural selection, an analysis of the large-scale properties of networks is necessary to reveal other relevant patterns that emerge through evolution. The difficulty in describing systems in biology, from protein-protein interaction networks to metabolic pathways, on a theoretical level has hampered the development of our understanding of biological networks. The goal of this project is to tackle the theme of emergent phenomena in biological complex networks with novel concepts from non-equilibrium systems and complexity, and to systematically transform these theoretical concepts into practically applicable models of functional modules. In order to achieve this goal, the PI will study functional modules (clusters of proteins cooperating towards achieving a given function) by clustering and renormalization methods. The intellectual merit of this project rests on the unique quantitative methodology, based on the self-similarity measure, developed to elucidate the evolutionary principles embodied at the level of networks of constituent molecules. This novel mathematical scheme will find wide applicability in the newly rising interdisciplinary fields at the interfaces of biology, sociology, and computer sciences. The broader impacts of this project include curriculum development, involvement of underrepresented minority students, and international and interdisciplinary collaborations. Promoting the involvement of minority undergraduate and graduate students in research environments will be a priority of this program. The project will also bring together international leading groups in Complexity and Statistical Physics, Bioinformatics, and Biology.

该项目的目的是了解生物网络获得模块化架构，稳健性和多种功能以维持生命的进化原理。尽管对自然选择的一般规则有很多了解，但对网络大规模特性的分析对于揭示通过进化出现的其他相关模式是必要的。从蛋白质 - 蛋白质相互作用网络到代谢途径，在理论层面上描述生物学系统的困难阻碍了我们对生物网络的理解的发展。该项目的目的是通过具有非平衡系统和复杂性的新颖概念来解决生物复杂网络中新兴现象的主题，并系统地将这些理论概念转变为实际上适用的功能模块模型。为了实现这一目标，PI将通过聚类和重新归一化方法研究功能模块（蛋白质合作实现给定功能的蛋白质簇）。该项目的智力优点取决于基于自相似度度量的独特定量方法，该方法是为了阐明在组成分子网络水平上所体现的进化原理。这个新颖的数学方案将在生物学，社会学和计算机科学界面的新上升跨学科领域中找到广泛的适用性。该项目的更广泛影响包括课程发展，代表性不足的少数族裔学生的参与以及国际和跨学科合作。促进少数族裔本科生和研究生参与研究环境将是该计划的优先事项。该项目还将在复杂性和统计物理学，生物信息学和生物学方面汇集国际领先团体。