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.
Highlights
Network pharmacology is based on systems biology and n etwork biology.It is possible to better understand the effec ts of cell and organ behavior on biological function at the molecular level of the system
The content of network pharmacology covers a variety of aspects,including a variety of omics,system biology, m ultidirectional pharmacology, network biology,computatio nal biology and biological analysis.Based on the drug-targ et -disease network,by analyzing the network topology,ke y protein function,drug disease network library and other existing information,Using professional network analysis software and algorithms, A systematic and holistic approa ch to reveal the mystery of disease-disease,disease phenot ype-target protein, target protein-drug and drug-drug.Obse rve the intervention and influence of drugs on diseases fro m the network level.Projecting drug targets into complex disease networks (Figure 1),revealing the mystery of co mplex drugs acting on the human body
Finding community structure and analyzing it is a very important way to understand the structure of various netw ork organizations in real life(Figure 2).It has been widely applied in biology, computer science and sociology,For example, the community structure in the social network e nables people to clearly understand some characteristics o r beliefs that they are different from other societies.In the biomolecular reaction network, Nodes aggregated togethe r to form functional modules often assume specific roles o r have specific functions.There are many algorithms to fin d the network community structure.Some classical algorit hms such as Graph Segmentation classical problems and c lustering analysis in sociology can be used for reference
Summary
Network pharmacology is based on systems biology and n etwork biology.It is possible to better understand the effec ts of cell and organ behavior on biological function at the molecular level of the system This method can speed up t he confirmation of drug targets and discover new drugs an d targets.,a combination of multi target drugs and dru gs with efficacy and safety can be designed. Finding community structure and analyzing it is a very important way to understand the structure of various netw ork organizations in real life(Figure 2).It has been widely applied in biology, computer science and sociology,For example, the community structure in the social network e nables people to clearly understand some characteristics o r beliefs that they are different from other societies.In the biomolecular reaction network, Nodes aggregated togethe r to form functional modules often assume specific roles o r have specific functions.There are many algorithms to fin d the network community structure.Some classical algorit hms such as Graph Segmentation classical problems and c lustering analysis in sociology can be used for reference
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