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A systematic survey of centrality measures for protein-protein interaction networks

机译:蛋白质-蛋白质相互作用网络集中度测量的系统调查

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摘要

BackgroundNumerous centrality measures have been introduced to identify “central” nodes in large networks. The availability of a wide range of measures for ranking influential nodes leaves the user to decide which measure may best suit the analysis of a given network. The choice of a suitable measure is furthermore complicated by the impact of the network topology on ranking influential nodes by centrality measures. To approach this problem systematically, we examined the centrality profile of nodes of yeast protein-protein interaction networks (PPINs) in order to detect which centrality measure is succeeding in predicting influential proteins. We studied how different topological network features are reflected in a large set of commonly used centrality measures.
机译:背景技术已经引入了许多集中度度量来识别大型网络中的“中心”节点。可以使用多种措施对有影响力的节点进行排名,从而让用户决定哪种措施最适合给定网络的分析。此外,网络拓扑对通过集中性度量对有影响的节点进行排名的影响还会使选择合适的度量变得更加复杂。为了系统地解决此问题,我们检查了酵母蛋白质-蛋白质相互作用网络(PPIN)节点的中心点特征,以检测哪种中心点方法成功预测了有影响力的蛋白质。我们研究了在大量常用的集中度度量中如何反映不同的拓扑网络特征。

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