[论文解读] The Diverse Club: The Integrative Core of Complex Networks

Maxwell A. Bertolero, B.T. Thomas Yeo+1 more|arXiv (Cornell University)|Jan 4, 2017

Neural dynamics and brain function参考文献 65被引用 65

一句话总结

本论文引入 diverse club（多样性社团），一组边广泛分布的节点，在跨多个真实世界网络中比传统的 rich club 更好地支持全局网络整合，并给出一个生成模型，显示 diverse 与 rich clubs 的不同进化压力。

ABSTRACT

A complex system can be represented and analyzed as a network, where nodes represent the units of the network and edges represent connections between those units. For example, a brain network represents neurons as nodes and axons between neurons as edges. In many networks, some nodes have a disproportionately high number of edges. These nodes also have many edges between each other, and are referred to as the rich club. In many different networks, the nodes of this club are assumed to support global network integration. However, another set of nodes potentially exhibits a connectivity structure that is more advantageous to global network integration. Here, in a myriad of different biological and man-made networks, we discover the diverse club--a set of nodes that have edges diversely distributed across the network. The diverse club exhibits, to a greater extent than the rich club, properties consistent with an integrative network function--these nodes are more highly interconnected and their edges are more critical for efficient global integration. Moreover, we present a generative evolutionary network model that produces networks with a diverse club but not a rich club, thus demonstrating that these two clubs potentially evolved via distinct selection pressures. Given the variety of different networks that we analyzed--the c. elegans, the macaque brain, the human brain, the United States power grid, and global air traffic--the diverse club appears to be ubiquitous in complex networks. These results warrant the distinction and analysis of two critical clubs of nodes in all complex systems.

研究动机与目标

• 推动在广为人知的 rich club 之外寻求整合网络核心的动机。
• 识别一个具有多样化连接的节点子集，提升在多样化网络中的全球整合。
• 展示 diverse club 在生物网络和人工网络中的普遍存在。
• 提出一个生成性进化模型，能够产生 diverse clubs 而不形成 rich clubs。

提出的方法

• 将 diverse club 定义为在网络中边分布多样的节点。
• 在全球整合方面比较 diverse club 与 rich club 的互连性和边缘关键性。
• 分析多种网络（如 C. elegans、macaque brain、human brain、US power grid、全球航空交通）以测试普遍性。
• 开发一个生成性的进化模型，产生具有 diverse club 的网络但不具有 rich club。
• 评估表明指示 diverse club 整合网络功能的属性。

实验结果

研究问题

• RQ1 是否存在一个边分布多样的节点集，能够比 rich club 更有效地支持全球网络整合？
• RQ2 相对于其 rich club 对应群， diverse clubs 是否展现出更高的互连性和边的关键性？
• RQ3 diverse clubs 是否在生物网络和人工网络中普遍存在？
• RQ4 生成性模型是否可以在不形成 rich club 的情况下产生具有 diverse club 的网络，暗示不同的进化压力？
• RQ5 diverse clubs 会对理解整合网络功能带来哪些影响？

主要发现

• diverse club 作为一组边分布多样的节点存在，其在对整合网络功能的对齐上优于 rich club。
• diverse club 中的节点彼此互连更紧密，且它们的边对实现全球高效整合更为关键。
• diverse club 出现在包括 C. elegans、macaque brain、human brain、US power grid 和全球航空交通等多样网络中。
• 一个生成性的进化模型可以在存在 diverse club 的同时不形成 rich club，从而暗示不同的选择压力。
• 结果主张在复杂系统中区分并分析两种关键节点社团（diverse 和 rich）。