Mapping change in large networks.

Mapping change in large networks.
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DOI:
10.1371/journal.pone.0008694
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发表时间:
2010-01-27
期刊:
影响因子:
3.7
通讯作者:
Bergstrom CT
Bergstrom CT
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Rosvall M;Bergstrom CT

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变化是生物学、技术、经济和科学本身相互作用模式的基本要素:生物体内部和生物体之间的相互作用发生变化;空中、陆地和海上运输模式都在发生变化;全球金融流动变化;以及科学研究前沿的变化。网络和聚类方法已成为理解这些大规模结构实例的重要工具,但如果没有区分真实趋势和噪声数据的方法,这些方法对于研究网络如何变化是没有用的。只有当我们能够赋予单个网络的划分重要性时,我们才能区分有意义的结构变化和随机波动。在这里,我们展示了伴随重要性聚类的引导重采样为这个问题提供了解决方案。为了将不断变化的结构与不断变化的网络功能联系起来,我们用冲积图来突出和总结显着的结构变化,并实现德索拉·普莱斯绘制科学变化图的愿景:研究过去十年约7000种科学期刊之间的引用模式,我们发现神经科学已经从一个跨学科专业转变为一门成熟的独立学科。
Change is a fundamental ingredient of interaction patterns in biology, technology, the economy, and science itself: Interactions within and between organisms change; transportation patterns by air, land, and sea all change; the global financial flow changes; and the frontiers of scientific research change. Networks and clustering methods have become important tools to comprehend instances of these large-scale structures, but without methods to distinguish between real trends and noisy data, these approaches are not useful for studying how networks change. Only if we can assign significance to the partitioning of single networks can we distinguish meaningful structural changes from random fluctuations. Here we show that bootstrap resampling accompanied by significance clustering provides a solution to this problem. To connect changing structures with the changing function of networks, we highlight and summarize the significant structural changes with alluvial diagrams and realize de Solla Price's vision of mapping change in science: studying the citation pattern between about 7000 scientific journals over the past decade, we find that neuroscience has transformed from an interdisciplinary specialty to a mature and stand-alone discipline.
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