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Repurposing\/repositioning of approved drugs offers a relatively low-cost and high-efficiency approach toward rapid development of efficacious treatments. The emergence of large-scale, heterogeneous biological networks has offered unprecedented opportunities for developing in silico drug repositioning approaches. However, capturing highly non-linear, heterogeneous network structures by most existing approaches for drug repositioning has been challenging.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>In this study, we developed a network-based deep-learning approach, termed deepDR, for in silico drug repurposing by integrating 10 networks: one drug\u2013disease, one drug-side-effect, one drug\u2013target and seven drug\u2013drug networks. Specifically, deepDR learns high-level features of drugs from the heterogeneous networks by a multi-modal deep autoencoder. Then the learned low-dimensional representation of drugs together with clinically reported drug\u2013disease pairs are encoded and decoded collectively via a variational autoencoder to infer candidates for approved drugs for which they were not originally approved. We found that deepDR revealed high performance [the area under receiver operating characteristic curve (AUROC) = 0.908], outperforming conventional network-based or machine learning-based approaches. Importantly, deepDR-predicted drug\u2013disease associations were validated by the ClinicalTrials.gov database (AUROC = 0.826) and we showcased several novel deepDR-predicted approved drugs for Alzheimer\u2019s disease (e.g. risperidone and aripiprazole) and Parkinson\u2019s disease (e.g. methylphenidate and pergolide).<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and implementation<\/jats:title><jats:p>Source code and data can be downloaded from https:\/\/github.com\/ChengF-Lab\/deepDR<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available online at Bioinformatics.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz418","type":"journal-article","created":{"date-parts":[[2019,5,14]],"date-time":"2019-05-14T19:42:18Z","timestamp":1557862938000},"page":"5191-5198","source":"Crossref","is-referenced-by-count":506,"title":["deepDR: a network-based deep learning approach to<i>in silico<\/i>drug repositioning"],"prefix":"10.1093","volume":"35","author":[{"given":"Xiangxiang","family":"Zeng","sequence":"first","affiliation":[{"name":"Department of Computer Science, Xiamen University , Xiamen 361005, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2552-2203","authenticated-orcid":false,"given":"Siyi","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Xiamen University , Xiamen 361005, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9885-1978","authenticated-orcid":false,"given":"Xiangrong","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Xiamen University , Xiamen 361005, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yadi","family":"Zhou","sequence":"additional","affiliation":[{"name":"Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruth","family":"Nussinov","sequence":"additional","affiliation":[{"name":"Computational Structural Biology Section, Basic Science Program, Frederick National Laboratory for Cancer Research, National Cancer Institute at Frederick , Frederick, MD 21702, USA"},{"name":"Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine , Tel Aviv University, Tel Aviv 69978, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1736-2847","authenticated-orcid":false,"given":"Feixiong","family":"Cheng","sequence":"additional","affiliation":[{"name":"Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic , Cleveland, OH 44195, USA"},{"name":"Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University , Cleveland, OH 44195, USA"},{"name":"Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine , Cleveland, OH 44106, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2019,5,22]]},"reference":[{"key":"2023013108382670100_btz418-B1","doi-asserted-by":"crossref","first-page":"878.","DOI":"10.15252\/msb.20156651","article-title":"Deep learning for computational biology","volume":"12","author":"Angermueller","year":"2016","journal-title":"Mol. 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