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In the study, therefore, we used the network of pharmacogenetic and bioinformatics to discuss the complex interactions in the top anti-cancer drugs with the help of computer high performance operating power and network visualization. We got a total of 81 known targets from the top 10 anti-cancer drugs. The shared most targets were from the 5-fluorouracil, capecitabine and tegafur, occupying 4, 4 and 3 targets, respectively. Based on complex network visual effect of the computer, gene set enrichment analysis displayed that the targets were mainly on five major categories. All the data showed that the two groups of drugs having some synergistic effects (5-fluorouracil, capecitabine, tegafur and tamoxifen, letrozole, respectively), which is suggests the top anti-cancer drugs\u2019 synergic existing in combination drugs on clinic.<\/jats:p>","DOI":"10.3233\/jifs-179402","type":"journal-article","created":{"date-parts":[[2019,9,24]],"date-time":"2019-09-24T14:55:38Z","timestamp":1569336938000},"page":"277-281","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Quickly evaluating the synergistic effects of top anti-cancer drugs by the computer high performance computing power and complex network visualization"],"prefix":"10.1177","volume":"38","author":[{"given":"Zhijun","family":"Zeng","sequence":"first","affiliation":[{"name":"Jiangxi Province Key Laboratory of TCM Etiopathogenisis, University of Jiangxi TCM, Nanchang, 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