Abstract: The study of complex network clustering methods has important theoretical significance and broad application prospects for analyzing the topological structure of complex networks, understanding the functions of complex networks, and predicting the behavior of complex networks. The current applications in complex biological networks are mainly concentrated in the areas of protein interaction network analysis and prediction of unknown protein functions, metabolic network analysis, protein similarity network analysis and gene regulation network analysis.Summary: The network cluster structure with small-world and scale-free statistical characteristics is one of the important topological properties of complex networks. The use of clustering algorithms in complex biological networks to reveal the cluster structure of biological networks is of great significance for analyzing the topology of biological networks and predicting their functions. References: https://aimed.protheragen.com/complex-network-analysis-service.html
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