从动力学揭示网络：导论
Revealing networks from dynamics: an introduction
摘要：
从复杂网络的集体动力学中，我们能学到什么关于其相互作用拓扑的知识？从非线性动力学的角度，我们简要回顾了最近的进展，如何推断结构连接（直接相互作用）从访问的动态单元。潜在的应用范围从物理学中的相互作用网络到化学和代谢反应、蛋白质和基因调控网络以及生物学中的神经电路和工程中的电功率电网或无线传感器网络。此外，我们简要地提到了一些标准的方法来推断有效的或功能性的连接。
英文摘要：
What can we learn from the collective dynamics of a complex network about its interaction topology? Taking the perspective from nonlinear dynamics, we briefly review recent progress on how to infer structural connectivity (direct interactions) from accessing the dynamics of the units. Potential applications range from interaction networks in physics, to chemical and metabolic reactions, protein and gene regulatory networks as well as neural circuits in biology and electric power grids or wireless sensor networks in engineering. Moreover, we briefly mention some standard ways of inferring effective or functional connectivity.
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