Dynamics of Complex Networks

9988674Barabasi在自然界的许多系统中，成分形成了一个高度互联的网络，提供了一个复杂的水平，使它们几乎无法用传统方法治疗。实例包括细胞中的代谢网络、社交网络、商业网络、万维网或因特网。 当代科学无法描述这些系统，目前限制了许多学科的进展，从分子生物学到计算机科学。本提案的目的是利用真实的网络上拓扑信息的日益增加的可用性来揭示确定网络拓扑的基本机制。我们的探索是由这样一种信念驱动的，即复杂网络的出现和演变是由许多系统共有的通用机制所控制的。为了实现我们的目标，我们提出了一个由三个步骤组成的研究计划。 首先，我们计划确定唯一表征网络拓扑结构的量，旨在开发一套措施，最终将使我们能够构建具有独特拓扑特性的网络。其次，我们计划研究普适性的概念：决定网络的标度指数和拓扑结构的机制是什么。第三，我们计划研究在何种程度上可以从部分拓扑信息重构网络。

9988674BarabasiIn many systems in Nature constituents form a highly interconnected network, offering a level of complexity that makes them practically untreatable with traditional methods. Examples include the metabolic network in a cell, social networks, business networks, the world wide web or the Internet. The inability of contemporary science to describe these systems currently limits advances in many disciplines, ranging from molecular biology to computer science. The objective of the present proposal is to capitalize on the increasing availability of topological information on real networks to uncover the basic mechanisms that determine the network topology. Our exploration is driven by the conviction that the emergence and the evolution of complex networks are governed by generic mechanisms that are common to many systems. To achieve our goal we propose a research program composed of three steps. First we plan to identify quantities that uniquely characterize the network topology, aiming to develop a set of measures, that eventually will allow us to construct a network with unique topological properties. Second, we plan to investigate the concept of universality: what are the mechanisms that determine the scaling exponents and the topology of the network. Third, we plan to study to which degree can a network be reconstructed from partial topological information.