{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,4]],"date-time":"2026-01-04T10:43:29Z","timestamp":1767523409849},"reference-count":46,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2023,9,22]],"date-time":"2023-09-22T00:00:00Z","timestamp":1695340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62172088"],"award-info":[{"award-number":["62172088"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007219","name":"Shanghai Natural Science Foundation","doi-asserted-by":"publisher","award":["21ZR1400400"],"award-info":[{"award-number":["21ZR1400400"]}],"id":[{"id":"10.13039\/100007219","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Drug combination therapy has gradually become a promising treatment strategy for complex or co-existing diseases. As drug\u2013drug interactions (DDIs) may cause unexpected adverse drug reactions, DDI prediction is an important task in pharmacology and clinical applications. Recently, researchers have proposed several deep learning methods to predict DDIs. However, these methods mainly exploit the chemical or biological features of drugs, which is insufficient and limits the performances of DDI prediction. Here, we propose a new deep multimodal feature fusion framework for DDI prediction, DMFDDI, which fuses drug molecular graph, DDI network and the biochemical similarity features of drugs to predict DDIs. To fully extract drug molecular structure, we introduce an attention-gated graph neural network for capturing the global features of the molecular graph and the local features of each atom. A sparse graph convolution network is introduced to learn the topological structure information of the DDI network. In the multimodal feature fusion module, an attention mechanism is used to efficiently fuse different features. To validate the performance of DMFDDI, we compare it with 10 state-of-the-art methods. The comparison results demonstrate that DMFDDI achieves better performance in DDI prediction. Our method DMFDDI is implemented in Python using the Pytorch machine-learning library, and it is freely available at https:\/\/github.com\/DHUDEBLab\/DMFDDI.git.<\/jats:p>","DOI":"10.1093\/bib\/bbad397","type":"journal-article","created":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T09:37:16Z","timestamp":1697535436000},"source":"Crossref","is-referenced-by-count":33,"title":["DMFDDI: deep multimodal fusion for drug\u2013drug interaction prediction"],"prefix":"10.1093","volume":"24","author":[{"given":"Yanglan","family":"Gan","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Donghua University , 2999 North Renmin Road, 201600, Shanghai , China"}]},{"given":"Wenxiao","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Donghua University , 2999 North Renmin Road, 201600, Shanghai , China"}]},{"given":"Guangwei","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Donghua University , 2999 North Renmin Road, 201600, Shanghai , China"}]},{"given":"Cairong","family":"Yan","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Donghua University , 2999 North Renmin Road, 201600, Shanghai , China"}]},{"given":"Guobing","family":"Zou","sequence":"additional","affiliation":[{"name":"School of Computer Engineering and Science, Shanghai University , 99 Shangda Road, 200444, Shanghai , China"}]}],"member":"286","published-online":{"date-parts":[[2023,11,2]]},"reference":[{"issue":"7","key":"2023110801101040300_ref1","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1016\/j.drudis.2016.05.015","article-title":"Drug combination therapy increases successful drug repositioning","volume":"21","author":"Sun","year":"2016","journal-title":"Drug Discov 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