{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T15:25:14Z","timestamp":1781191514004,"version":"3.54.1"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T00:00:00Z","timestamp":1742860800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T00:00:00Z","timestamp":1742860800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-025-95372-5","type":"journal-article","created":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T02:02:43Z","timestamp":1742954563000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Drug repositioning model based on knowledge graph embedding"],"prefix":"10.1038","volume":"15","author":[{"given":"Shufang","family":"He","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyu","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,3,25]]},"reference":[{"issue":"4","key":"95372_CR1","doi-asserted-by":"crossref","first-page":"S103","DOI":"10.1164\/ajrccm.156.4.12-tac-5","volume":"156","author":"NJ Schork","year":"1997","unstructured":"Schork, N. J. Genetics of complex disease: Approaches, problems, and solutions. Am. J. Respir. Crit Care Med. 156 (4), S103\u2013S109 (1997).","journal-title":"Am. J. Respir. Crit Care Med."},{"key":"95372_CR2","unstructured":"Steedman, M. & Taylor, K. Measuring the return from pharmaceutical innovation. Deloitte Center for Healthcare Solutions, Deloitte. (2019). https:\/\/www2.deloitte.com\/us\/en\/pages\/life-sciences-and-health-care\/articles\/measuring-return-from-pharmaceutical-innovation.html"},{"key":"95372_CR3","unstructured":"Di, M., Joseph, A., Henry, G., Grabowski & Ronald, W. H. Innovation in the pharmaceutical industry: New estimates of R&D costs. Journal of Health Economics. North-Holland, February 12, \u200c (2016)."},{"issue":"22","key":"95372_CR4","first-page":"2541","volume":"29","author":"YF Tai","year":"2020","unstructured":"Tai, Y. F., Wang, S., Zhang, F. L., Yu, Q. & He, P. F. The main topics and development context of drug repositioning research in China. Chin. J. New. Drugs. 29 (22), 2541\u20132551 (2020).","journal-title":"Chin. J. New. Drugs"},{"issue":"Database issue","key":"95372_CR5","first-page":"D1060","volume":"39","author":"EV Joachim","year":"2011","unstructured":"Joachim, E. V., Mathias, S. M. M. & Soeren, D. Robert, P. PROMISCUOUS: A database for network-based drug-repositioning. Nucleic Acids Res. 39 (Database issue), D1060\u2013D1066 (2011).","journal-title":"Nucleic Acids Res."},{"issue":"5","key":"95372_CR6","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/j.tips.2013.03.004","volume":"34","author":"N Novac","year":"2013","unstructured":"Novac, N. Challenges and opportunities of drug repositioning. Trends Pharmacol. Sci. 34 (5), 267\u2013272 (2013).","journal-title":"Trends Pharmacol. Sci."},{"issue":"7793","key":"95372_CR7","first-page":"d741","volume":"342","author":"SA F","year":"2011","unstructured":"F, S. A. Old drugs, new tricks. BMJ 342 (7793), d741 (2011). Clinical research ed.","journal-title":"BMJ"},{"issue":"04","key":"95372_CR8","first-page":"294","volume":"38","author":"SZ Shan","year":"2024","unstructured":"Shan, S. Z., Wen, B., Qiao, T. C. & Shan, G. C. Application and analysis of problems of artificial intelligence in drug repurposing for Corona virus disease 2019 (COVID-19). Chin. J. Pharmacol. Toxicol. 38 (04), 294\u2013303 (2024).","journal-title":"Chin. J. Pharmacol. Toxicol."},{"issue":"12","key":"95372_CR9","first-page":"3150","volume":"38","author":"SM Yang","year":"2023","unstructured":"Yang, S. M., Yu, J., Hou, W. B., Zhao, Q. & Li, Y. L. Research progress on artificial intelligence algorithms for drug discovery. Drugs Clin. 38 (12), 3150\u20133160 (2023).","journal-title":"Drugs Clin."},{"issue":"3","key":"95372_CR10","first-page":"282","volume":"54","author":"ZH Yu","year":"2023","unstructured":"Yu, Z. H. et al. Artificial intelligence-based drug development: Current progress and future challenges. J. China Pharm. Univ. 54 (3), 282\u2013293 (2023).","journal-title":"J. China Pharm. Univ."},{"issue":"9","key":"95372_CR11","first-page":"2030","volume":"46","author":"SX Li","year":"2023","unstructured":"Li, S. X. et al. Research progress in application of artificial intelligence during process of drug discovery. Drug Evaluat. Res. 46 (9), 2030\u20132036 (2023).","journal-title":"Drug Evaluation Res."},{"issue":"1","key":"95372_CR12","doi-asserted-by":"crossref","first-page":"12807","DOI":"10.1038\/s41598-024-63561-3","volume":"14","author":"S Vishakha","year":"2024","unstructured":"Vishakha, S., Kumar, S. S. & Ritesh, S. A novel framework based on explainable AI and genetic algorithms for designing neurological medicines. Sci. Rep. 14 (1), 12807\u201312807 (2024).","journal-title":"Sci. Rep."},{"key":"95372_CR13","doi-asserted-by":"crossref","unstructured":"Barberis, A., Aerts, H. J. W. L. & Buffa, F. M. Robustness and reproducibility for AI learning in biomedical sciences: RENOIR..Sci. Rep. 14(1), 1933\u20131933 (2024).","DOI":"10.1038\/s41598-024-51381-4"},{"issue":"3","key":"95372_CR14","doi-asserted-by":"crossref","first-page":"2026","DOI":"10.3390\/ijms24032026","volume":"24","author":"S Chayna","year":"2023","unstructured":"Chayna, S. et al. Artificial intelligence and machine learning technology driven modern drug discovery and Development. Int. J. Mol. Sci. 24 (3), 2026\u20132026 (2023).","journal-title":"Int. J. Mol. Sci."},{"key":"95372_CR15","unstructured":"E, G. D. et al. A SARS-CoV-2-Human protein-protein interaction map reveals drug targets and potential drug-repurposing. bioRxiv: the preprint server for biology (2020)."},{"issue":"4","key":"95372_CR16","doi-asserted-by":"crossref","first-page":"e25754","DOI":"10.1016\/j.heliyon.2024.e25754","volume":"10","author":"S Ashique","year":"2024","unstructured":"Ashique, S. et al. Application of artificial intelligence (AI) to control COVID-19 pandemic: Current status and future prospects. Heliyon 10 (4), e25754 (2024).","journal-title":"Heliyon"},{"issue":"3","key":"95372_CR17","doi-asserted-by":"crossref","first-page":"109148","DOI":"10.1016\/j.isci.2024.109148","volume":"27","author":"HM Luo","year":"2024","unstructured":"Luo, H. M. et al. Drug-drug interactions prediction based on deep learning and knowledge graph: A review. iScience 27 (3), 109148 (2024).","journal-title":"iScience"},{"key":"95372_CR18","doi-asserted-by":"crossref","unstructured":"Feng, Y. et al. A medical image segmentation network based on Spatial pyramid and attention mechanism. Biomed. Signal Process. Control, 94106285 (2024).","DOI":"10.2139\/ssrn.4618385"},{"issue":"PB","key":"95372_CR19","doi-asserted-by":"crossref","first-page":"106561","DOI":"10.1016\/j.bspc.2024.106561","volume":"96","author":"J Di","year":"2024","unstructured":"Di, J. et al. A multimodal medical image fusion method based on an attention mechanism and MobileNetV3. Biomed. Signal Process. Control. 96 (PB), 106561 (2024).","journal-title":"Biomed. Signal Process. Control"},{"key":"95372_CR20","unstructured":"Zu, J., Qian, J. T., Wang, Y. & Gu, Y. X. Drug repositioning method and system based on word vector representation and attention mechanism. Shanxi Province: CN202210582908.2, 2024-04-19."},{"key":"95372_CR21","unstructured":"Tang, X. F. et al. A drug repositioning method and system based on bilinear attention network. Hubei Province: CN202311259470.5, 2023\u20132011."},{"issue":"4","key":"95372_CR22","first-page":"52","volume":"31","author":"ZQ Guo","year":"2023","unstructured":"Guo, Z. Q., Tan, Z. F., Wang, J. J. & Ye, Q. Intelligent Q&A of proprietary Chinese medicine based on knowledge graph. Comput. Inform. Technol. 31 (4), 52\u201357 (2023).","journal-title":"Comput. Inform. Technol."},{"issue":"3","key":"95372_CR23","first-page":"160","volume":"21","author":"D Wu","year":"2022","unstructured":"Wu, D. & Zhou, Z. J. Intelligent question answering system for cardiovascular diseases based on knowledge Graph. Softw. Guide. 21 (3), 160\u2013164 (2022).","journal-title":"Softw. Guide"},{"key":"95372_CR24","unstructured":"Remy, C. et al. LORD: a phenotype-genotype semantically integrated biomedical data tool to support rare disease diagnosis coding in health information systems.. AMIA Annual Symposium proceedings. AMIA Symposium. 2015434-440. (2015)."},{"issue":"9","key":"95372_CR25","doi-asserted-by":"crossref","first-page":"e38414","DOI":"10.2196\/38414","volume":"10","author":"H Weng","year":"2022","unstructured":"Weng, H., Chen, J. L., Ou, A. & Lao, Y. R. Leveraging representation learning for the construction and application of a knowledge graph for traditional Chinese medicine: Framework development study. JMIR Med. Inf. 10 (9), e38414\u2013e38414 (2022).","journal-title":"JMIR Med. Inf."},{"issue":"4","key":"95372_CR26","first-page":"18","volume":"30","author":"ZX Fu","year":"2023","unstructured":"Fu, Z. X. et al. Research on viscera syndrome differentiation in TCM based on multiple link prediction Reasoning. Chin. J. Inform. Tradit. Chin. Med. 30 (4), 18\u201324 (2023).","journal-title":"Chin. J. Inform. Traditional Chin. Med."},{"key":"95372_CR27","doi-asserted-by":"crossref","unstructured":"Li, J., Gao, J., Feng, B. Y. & Jing, Y. PlagueKD: A knowledge graph-based plague knowledge database.. Database J. Biol. Databases Curat. 2022. (2022).","DOI":"10.1093\/database\/baac100"},{"key":"95372_CR28","unstructured":"Lu, Y. W. Construction of gastric cancer knowledge graph and drug discovery application. Soochow Univ. (2023)."},{"issue":"5","key":"95372_CR29","first-page":"796","volume":"38","author":"YH Lyu","year":"2024","unstructured":"Lyu, Y. H., Zhao, H. X., Li, Q., Liang, A. X. & Yu, Q. Drug knowledge discovery for autism spectrum disorders based on SPO predications. Chin. Nurs. Res. 38 (5), 796\u2013804 (2024).","journal-title":"Chin. Nurs. Res."},{"issue":"24","key":"95372_CR30","first-page":"64","volume":"29","author":"M Fan","year":"2023","unstructured":"Fan, M. & Gao, Y. Visualization construction of knowledge graph based on Tibetan medicine data. Mod. Comput. 29 (24), 64\u201368 (2023).","journal-title":"Mod. Comput."},{"key":"95372_CR31","doi-asserted-by":"crossref","unstructured":"Ouzounis, S. et al. Data-driven drug repurposing in diabetes mellitus through an enhanced knowledge graph. Eng. Proc. 50(1), 9 (2023).","DOI":"10.3390\/engproc2023050009"},{"key":"95372_CR32","unstructured":"Xi, C. C. The Kidney Life Gate Theory of the Warming and Supplementing School in Ming Dynasty and its Inheritance and Development To Huangdi Neijing[D] (Beijing University of Chinese Medicine, 2021)."},{"issue":"3","key":"95372_CR33","first-page":"64","volume":"31","author":"Q Wang","year":"2024","unstructured":"Wang, Q., Dai, G. H., Guan, H. & Gao, W. L. Construction and application of clinical experience knowledge graph for renowned TCM Doctors in treating coronary heart disease. Chin. J. Inform. Tradit. Chin. Med. 31 (3), 64\u201370 (2024).","journal-title":"Chin. J. Inform. Traditional Chin. Med."},{"key":"95372_CR34","doi-asserted-by":"crossref","unstructured":"Xiong, W. P. et al. Design and evaluation of a prescription drug monitoring program for Chinese patent medicine based on knowledge Graph. Evid.-Based Complement. Altern. Med., 20219970063\u201320219970063. (2021).","DOI":"10.1155\/2021\/9970063"},{"issue":"12","key":"95372_CR35","doi-asserted-by":"crossref","first-page":"2724","DOI":"10.1109\/TKDE.2017.2754499","volume":"29","author":"Q Wang","year":"2017","unstructured":"Wang, Q., Mao, Z. D., Wang, B. & Guo, L. Knowledge graph embedding: A survey of approaches and Applications. IEEE Trans. Knowl. Data Eng. 29 (12), 2724\u20132743 (2017).","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"6","key":"95372_CR36","first-page":"931","volume":"19","author":"JJ Dai","year":"2022","unstructured":"Dai, J. J., Shi, L. J., Huang, X. Q. & Chen, M. Y. Construction and application of diseases and drugs correlation knowledge map based on Spark. Chin. J. Health Inf. Manag. 19 (6), 931\u2013938 (2022).","journal-title":"Chin. J. Health Inf. Manage."},{"issue":"007","key":"95372_CR37","first-page":"1929","volume":"035","author":"KQ Yuan","year":"2018","unstructured":"Yuan, K. Q., Deng, Y., Chen, D. Y., Zhang, B. & Lei, K. Construction techniques and research development of medical knowledge graph. Appl. Res. Comput. 035 (007), 1929\u20131936 (2018).","journal-title":"Appl. Res. Comput."},{"key":"95372_CR38","unstructured":"Yang, B. S., Yih, W. T., He, X. D., Gao, J. F. & Deng, L. Embedding entities and relations for learning and inference in knowledge Bases. CoRR, (2014)."},{"key":"95372_CR39","doi-asserted-by":"crossref","unstructured":"Zheng, D. et al. DGL-KE: training knowledge graph embeddings at Scale. 739\u2013748. (2020).","DOI":"10.1145\/3397271.3401172"},{"issue":"10","key":"95372_CR40","first-page":"33","volume":"27","author":"XL Xiu","year":"2018","unstructured":"Xiu, X. L., Wu, S. Z., Cui, J. W., Wu, J. M. & Qian, Q. Advances in studies on construction of medical knowledge graphs. Chin. J. Med. Libr. Inform. Sci. 27 (10), 33\u201339 (2018).","journal-title":"Chin. J. Med. Libr. Inform. Sci."},{"issue":"2","key":"95372_CR41","first-page":"247","volume":"53","author":"ZY Liu","year":"2016","unstructured":"Liu, Z. Y., Sun, M. S., Lin, Y. K. & Xie, R. B. Knowledge representation learning: A review. J. Comput. Res. Dev. 53 (2), 247\u2013261 (2016).","journal-title":"J. Comput. Res. Dev."},{"issue":"2","key":"95372_CR42","first-page":"65","volume":"6","author":"P Ghasemiyeh","year":"2020","unstructured":"Ghasemiyeh, P. & Samani, S. M. Iron chelating agents: Promising supportive therapies in severe cases of COVID-19?. Trends Pharm. Sci. 6 (2), 65\u201366 (2020).","journal-title":"Trends Pharm. Sci."},{"issue":"5","key":"95372_CR43","first-page":"659","volume":"52","author":"X Qi","year":"2023","unstructured":"Qi, X. et al. Exploration of therapeutic drugs for gastric cancer using drug repositioning strategy. J. Univ. Electron. Sci. Technol. China. 52 (5), 659\u2013666 (2023).","journal-title":"J. Univ. Electron. Sci. Technol. China"},{"issue":"5","key":"95372_CR44","doi-asserted-by":"crossref","first-page":"1817","DOI":"10.1021\/acs.jmedchem.6b01507","volume":"60","author":"WQ Lu","year":"2017","unstructured":"Lu, W. Q. et al. Drug repurposing of histone deacetylase inhibitors that alleviate neutrophilic inflammation in acute lung injury and idiopathic pulmonary fibrosis via inhibiting leukotriene A4 hydrolase and blocking LTB4 Biosynthesis. J. Med. Chem. 60 (5), 1817\u20131828 (2017).","journal-title":"J. Med. Chem."},{"issue":"1","key":"95372_CR45","first-page":"4","volume":"44","author":"C Peng","year":"2020","unstructured":"Peng, C., Hu, Y. X., Chen, L. F., Ye, Z. X. & Tian, G. A. Review on in-silico repositioning algorithms of drugs and chemical compounds. Progr. Pharm. Sci. 44 (1), 4\u20139 (2020).","journal-title":"Progress Pharm. Sci."},{"issue":"3","key":"95372_CR46","first-page":"114","volume":"42","author":"F Chen","year":"2024","unstructured":"Chen, F., Yang, C. R., Zhang, Z., Chen, F. & Liu, X. Establishment of a high-throughput screening platform based on drug repurposing targeting alpha-1-acid glycoprotein and discovery of potential weight loss drugs. J. Pharm. Pract. Serv. 42 (3), 114\u2013120 (2024).","journal-title":"J. Pharm. Pract. Service"}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-95372-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-95372-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-95372-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T02:04:51Z","timestamp":1742954691000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-025-95372-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,25]]},"references-count":46,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["95372"],"URL":"https:\/\/doi.org\/10.1038\/s41598-025-95372-5","relation":{},"ISSN":["2045-2322"],"issn-type":[{"value":"2045-2322","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,25]]},"assertion":[{"value":"25 December 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 March 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 March 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"10298"}}