Dissecting evolving interaction networks: Which network components are important for the dynamics?

在几乎所有尺度的有生命和无生命的自然界中，都可以发现复杂的网络。例子包括相互连接的蜂窝结构(例如大脑)、通信(例如互联网)和基础设施网络(例如空中交通、电网)、社会网络，甚至气候网络。对复杂网络的跨学科研究已经从对不同尺度上的网络性质的刻画发展到通过演化的相互作用网络来提高我们对集体动力学现象的理解。尽管如此，解开结构和动力学之间的复杂关系仍然是一个挑战，主要是因为目前在识别进化相互作用网络的关键组成部分(节点和链路)方面的进展受到许多因素的限制。我们提出了一个研究计划，旨在改进(1)对网络结构和动力学重要的组成部分的识别和(2)对这些关键组成部分的属性的表征。通过面向应用的方法开发和计算机模拟以及对真实世界网络的分析，我们的目的是促进我们对自然和人造进化相互作用网络中结构和动力学之间关系的局部方面的理解。

Complex networks can be found in animate and inanimate nature on virtually all scales. Examples include interconnected cellular structures (e.g. the brain), communication (e.g. the Internet) and infrastructure networks (e.g., air traffic, power grid), social, and even climate networks. Interdisciplinary research into complex networks has advanced from a characterization of network properties on various scales to improving our understanding of collective dynamical phenomena by means of evolving interaction networks. Still, disentangling the complicated relationship between structure and dynamics remains a challenge, mostly because progress in identifying key constituents (nodes and links) of evolving interaction networks is currently limited by a number of factors.We propose a research programme that targets at improving (1) the identification of constituents that are important for the network's structure and dynamics and (2) the characterization of properties of such key constituents. By means of application-oriented method developments and computer simulations as well as through analyses of real-world networks, we aim at advancing our understanding of local aspects of the relationship between structure and dynamics in natural and man-made evolving interaction networks.