文献类型：期刊文献

英文题名：Drug Repurposing for Newly Emerged Diseases via Network-based Inference on a Gene-disease-drug Network

作者：Qin, Li[1];Wang, Jiye[1];Wu, Zengrui[1];Li, Weihua[1];Liu, Guixia[1];Tang, Yun[1]

机构：[1]East China Univ Sci & Technol, Sch Pharm, Shanghai Frontiers Sci Ctr Optogenet Tech Cell Me, Shanghai 200237, Peoples R China

年份：2022

卷号：41

期号：9

外文期刊名：MOLECULAR INFORMATICS

收录：;EI(收录号：20232414226134);WOS:【SCI-EXPANDED(收录号:WOS:000778967800001)】；

基金：This work was supported by the National Key Research and Development Program of China (Grant 2019YFA0904800), the National Natural Science Foundation of China (Grants 81872800, 82173746 and 82104066), and Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism (Shanghai Municipal Education Commission, Grant 2021 Sci & Tech 03-28).

语种：英文

外文关键词：Drug repurposing; Disease-drug associations; Network-based inference

摘要：Identification of disease-drug associations is an effective strategy for drug repurposing, especially in searching old drugs for newly emerged diseases like COVID-19. In this study, we put forward a network-based method named NEDNBI to predict disease-drug associations based on a gene-disease-drug tripartite network, which could be applied in drug repurposing. The novelty of our method lies in the fact that no negative data are required, and new disease could be added into the disease-drug network with gene as the bridge. The comprehensive evaluation results showed that the proposed method had good performance, with AUC value 0.948 +/- 0.009 for 10-fold cross validation. In a case study, 8 of the 20 predicted old drugs have been tested clinically for the treatment of COVID-19, which illustrated the usefulness of our method in drug repurposing. The source code and data of the method are available at .