Drug addiction is a chronic recurrent brain disease. Its formation mechanism is that individuals repeatedly use drugs. The chemical composition of drugs directly affects the brain, extensively changes the structure and function of the brain's influence on the brain nervous system, and further promotes drug seeking and drug taking behavior, ultimately leading to the occurrence of addiction disorder.
Analyzing drug addiction datasets is crucial as it provides important insights into understanding the mechanisms of drug addiction and exploring potential biomarkers of drug addiction.The drug addiction database analyzed and presented multiple datasets of addictive drugs, including human and mouse, distributed in different brain regions. In this database, the differential expression of different addictive drugs in different brain regions can be queried, and a differential gene protein interaction network has been constructed. Twelve different centrality algorithms have been used to calculate the centrality of nodes in the network, and possible key genes have been screened. Finally, enrichment analysis has been conducted on the genes in the network.
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