Comparative Study Of Complex Network Community Structure Algorithms In network Pharmacology Analysis

Abstract

Community structure is an extremely important characteristic of complex networks composed of network pharmacology. The mining of network community structure is of great importance in many fields such as biology, computer science and sociology. In recent years, for different types of large-scale complex networks, researchers had proposed many algorithms for finding community structures. This paper reviewed some of the most representative algorithms in the field of network pharmacology, and focused on the analysis of the improved algorithms based on the modularity index and the new algorithms that could reflect the level and overlap of the community. Finally, a benchmark was established to measure the quality of the community classification algorithm.