ITR: A Twin-Framework To Analyze, Model and Design Robust, Complex Networks Using Biological and Computational Principles

EIA-0205061 Ray，Animesh Keck研究生院标题：一个双框架来分析，建模和设计鲁棒的，复杂的网络使用生物和计算原理自然网络（如互联网，电源电网或细胞的基因调控电路）的脆弱性意外或故意攻击是一个重要的研究领域。到目前为止，大多数工作都集中在现有的静态网络的观察或计算机模拟，因为大多数自然网络是很难操纵实验。 芽殖酵母是一种单细胞生物体，其细胞核中调节RNA分子合成的复杂分子机制是自然网络的一个真实实例，可以通过定义的遗传操作在实验上对其进行扰动，并且可以通过当前的基因组技术在分子水平上以前所未有的准确度研究这些扰动的结果。 该项目的目标是开发一个生物驱动的计算框架，用于网络鲁棒性。 为了实现这一目标，一个足够复杂的生物试验床，酵母中孢子形成的基因调控网络，已被采用作为实验网络模型。 系统性基因敲除突变（相当于节点移除）和调控位点缺失突变（相当于边缘移除）正被用作主动改变网络的工具。这些扰动的影响，在基因调控网络架构正在分析在全基因组转录谱的水平。 目前正在为大规模网络开发通用数据模型。 利用该数据模型对生物网络的相关实验行为进行了仿真。 通过进化选择的复杂网络架构的设计原则正在通过数学建模和测试进行探索。从这些研究中获得的见解将是有价值的防御战略，在复杂的网络设计，在通信技术，灾难响应，以及设计强大的通信基础设施抵抗有计划的攻击的影响。

EIA- 0205061Ray, Animesh Keck Graduate Institute TITLE: A Twin-Framework To Analyze, Model and Design Robust, Complex Networks Using Biological and Computational PrinciplesVulnerability of natural networks (such as the Internet, power supply grid, or gene regulatory circuits of cells) to accidental or deliberate attack is an important area of study. To date most work has focused on observations of existing static networks or on computer simulations, because most natural networks are difficult to manipulate experimentally. The complex molecular machinery regulating the synthesis of RNA molecules in the nucleus of budding yeast, a single-celled organism, is a real-world instance of a natural network that can be experimentally perturbed by defined genetic manipulations, and the results of these perturbations can be studied at the molecular level with unprecedented accuracy by current genomic techniques. The goal of this project is to develop a biology-driven computational framework for network robustness. To achieve this goal, a biological test-bed of sufficiently complexity, the gene regulatory network of sporulation in yeast, has been adopted as an experimental network model. Systematic gene knockout mutations (equivalent to node removal), and regulatory site deletion mutations (equivalent to edge removal), are being used as tools to actively alter the network. Effects of these perturbations in the gene regulatory network architecture are being analyzed at the level of whole-genome transcriptional profiles. A generic data model for large-scale networks is being developed. The relevant experimental behavior of the biological network is being emulated with the data model. Design principles underlying the architecture of complex networks selected through evolution are being probed through mathematical modeling and testing. Insights obtained from these studies will be valuable for defensive strategies in complex network design, with implications in, among others, communication technology, disaster response, and in designing robust communication infrastructure resistant to planned attacks.