Finding and analysing the minimum set of driver nodes required to control multilayer networks
Finding and analysing the minimum set of driver nodes required to control multilayer networks
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DOI：
10.1038/s41598-018-37046-z
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发表时间：
2019-01-24
影响因子：
4.6
通讯作者：
Akutsu, Tatsuya
中科院分区：
文献类型：
--
作者：
Nacher, Jose C.;Ishitsuka, Masayuki;Akutsu, Tatsuya
在现实世界的复杂情况下，很难控制多层网络。在这里，我们首先定义的多层控制问题的最小支配集（MDS）的可控性框架和数学证明，简单的公式可以用来估计的最小支配集在多层（MDSM）复杂网络的大小。其次，我们开发了一种新的算法，有效地识别MDSM在多达6层，在每层网络中有几千个节点。有趣的是，研究结果显示，类似网络的MDSM大小与控制单个网络所需的MDSM大小没有显着差异。这一结果开辟了未来的方向，例如，通过识别一组共同的酶或蛋白质用于药物靶向来控制多个物种。我们将我们的方法应用于主要植物谱系的70个全基因组代谢网络，揭示了多层网络中的可控性与基因组规模的代谢功能之间的一些关系。
It is difficult to control multilayer networks in situations with real-world complexity. Here, we first define the multilayer control problem in terms of the minimum dominating set (MDS) controllability framework and mathematically demonstrate that simple formulas can be used to estimate the size of the minimum dominating set in multilayer (MDSM) complex networks. Second, we develop a new algorithm that efficiently identifies the MDSM in up to 6 layers, with several thousand nodes in each layer network. Interestingly, the findings reveal that the MDSM size for similar networks does not significantly differ from that required to control a single network. This result opens future directions for controlling, for example, multiple species by identifying a common set of enzymes or proteins for drug targeting. We apply our methods to 70 genome-wide metabolic networks across major plant lineages, unveiling some relationships between controllability in multilayer networks and metabolic functions at the genome scale.