Collaborative Research: Dynamics of Boolean Networks and Gene Expression

合作研究：布尔网络和基因表达的动力学

• 批准号: 0417372
• 负责人: Joshua Socolar
• 金额: --
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0417372&HistoricalAwards=false
• 关键词: Collaborative; Research; Dynamics; Boolean; Networks

This research project focuses on the generic properties of complex networks, with the goal of elucidating the functional implications of different types of network architecture. The working hypothesis is that certain classes of Boolean networks illustrate principles of organization that underlie the structure of biological organisms. Such networks are known to exhibit fundamentally distinct regimes of behavior: ordered, chaotic, and critical. Do biological cells belong to one of these classes? Modern gene array techniques now permit the gathering of vast amounts of data on gene expression, providing a new experimental window on questions of this type. The proposed research aims to develop a useful theoretical framework for designing such experiments and interpreting their results. Specific aims of the project include the determination of scaling laws for cascades of activity following perturbations in scale-free and modular Boolean networks, the characterization of sets of dynamical attractors, and transitions between them, associated with different network architectures, and the analysis of such networks when stochastic timing rules are employed for updating rather than the traditional synchronous updating rules. In all cases, attention will be focused on quantities that can be measured in biological systems, and currently available experimental data will be used to refine the classes of models to be studied.The project is highly cross-disciplinary, requiring a collaboration between experts in dynamical systems theory and cell and developmental biology. Funds will be used to provide interdisciplinary training for an undergraduate student, a graduate student, and a postdoc in the burgeoning fields of functional genomics and bioinformatics, where analytical skills traditionally taught in physics contexts and principles of cell and molecular biology are equally important.

本研究项目关注复杂网络的一般属性，目的是阐明不同类型的网络体系结构的功能含义。工作假设是，某些类型的布尔网络说明了构成生物有机体结构的组织原则。众所周知，这样的网络表现出从根本上不同的行为机制：有序、混乱和关键。生物细胞是否属于这些类别之一？现代基因阵列技术现在允许收集关于基因表达的海量数据，为这类问题提供了一个新的实验窗口。这项拟议的研究旨在开发一个有用的理论框架来设计这样的实验并解释他们的结果。该项目的具体目标包括确定无标度和模块化布尔网络中扰动后的活动级联的标度律，描述与不同网络体系结构相关联的动态吸引子集以及它们之间的转换，以及当使用随机定时规则而不是传统的同步更新规则进行更新时，对这种网络进行分析。在所有情况下，注意力都将集中在生物系统中可以测量的量上，目前可用的实验数据将用于改进要研究的模型类别。该项目具有高度跨学科的特点，需要动力系统理论专家与细胞和发育生物学专家之间的合作。资金将用于在新兴的功能基因组学和生物信息学领域为本科生、研究生和博士后提供跨学科培训，在这些领域，传统上在物理学背景下教授的分析技能以及细胞和分子生物学的原理同样重要。