Max Planck Institute for Mathematics in the Sciences, 04103, Leipzig, Germany.
Bioinformatics Group, Department of Computer Science, Universität Leipzig, 04107, Leipzig, Germany.
Theory Biosci. 2020 Dec;139(4):337-348. doi: 10.1007/s12064-020-00328-0. Epub 2020 Nov 20.
The relations, rather than the elements, constitute the structure of networks. We therefore develop a systematic approach to the analysis of networks, modelled as graphs or hypergraphs, that is based on structural properties of (hyper)edges, instead of vertices. For that purpose, we utilize so-called network curvatures. These curvatures quantify the local structural properties of (hyper)edges, that is, how, and how well, they are connected to others. In the case of directed networks, they assess the input they receive and the output they produce, and relations between them. With those tools, we can investigate biological networks. As examples, we apply our methods here to protein-protein interaction, transcriptional regulatory and metabolic networks.
关系而非元素构成了网络的结构。因此,我们开发了一种系统的方法来分析网络,将其建模为图或超图,该方法基于(超)边的结构属性,而不是基于顶点。为此,我们利用所谓的网络曲率。这些曲率量化了(超)边的局部结构属性,即它们与其他边的连接方式和连接程度。在有向网络的情况下,它们评估所接收的输入和产生的输出以及它们之间的关系。有了这些工具,我们就可以研究生物网络。作为示例,我们在这里将我们的方法应用于蛋白质-蛋白质相互作用、转录调控和代谢网络。