{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T05:38:28Z","timestamp":1775799508544,"version":"3.50.1"},"reference-count":50,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T00:00:00Z","timestamp":1588550400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61702421"],"award-info":[{"award-number":["61702421"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1811262"],"award-info":[{"award-number":["U1811262"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772426"],"award-info":[{"award-number":["61772426"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"The international Postdoctoral Fellowship Program","award":["20180029"],"award-info":[{"award-number":["20180029"]}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2017M610651"],"award-info":[{"award-number":["2017M610651"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2016YFC0901605"],"award-info":[{"award-number":["2016YFC0901605"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018537","name":"National Science and Technology Major Project","doi-asserted-by":"crossref","award":["2016YFC1202302"],"award-info":[{"award-number":["2016YFC1202302"]}],"id":[{"id":"10.13039\/501100018537","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,3,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Identification of new drug\u2013target interactions (DTIs) is an important but a time-consuming and costly step in drug discovery. In recent years, to mitigate these drawbacks, researchers have sought to identify DTIs using computational approaches. However, most existing methods construct drug networks and target networks separately, and then predict novel DTIs based on known associations between the drugs and targets without accounting for associations between drug\u2013protein pairs (DPPs). To incorporate the associations between DPPs into DTI modeling, we built a DPP network based on multiple drugs and proteins in which DPPs are the nodes and the associations between DPPs are the edges of the network. We then propose a novel learning-based framework, \u2018graph convolutional network (GCN)-DTI\u2019, for DTI identification. The model first uses a graph convolutional network to learn the features for each DPP. Second, using the feature representation as an input, it uses a deep neural network to predict the final label. The results of our analysis show that the proposed framework outperforms some state-of-the-art approaches by a large margin.<\/jats:p>","DOI":"10.1093\/bib\/bbaa044","type":"journal-article","created":{"date-parts":[[2020,3,9]],"date-time":"2020-03-09T20:19:57Z","timestamp":1583785197000},"page":"2141-2150","source":"Crossref","is-referenced-by-count":292,"title":["Identifying drug\u2013target interactions based on graph convolutional network and deep neural network"],"prefix":"10.1093","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1913-081X","authenticated-orcid":false,"given":"Tianyi","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Computer Science at Harbin Institute of Technology. He currently works as a bioinformatician in Beth Israel Deaconess Medical Center"}]},{"given":"Yang","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Life Science at Harbin Institute of Technology. His expertise is bioinformatics"}]},{"given":"Linda R","family":"Valsdottir","sequence":"additional","affiliation":[{"name":"MS in Biology and works as a scientific writer at the Smith Center for Outcomes Research in Cardiology at Beth Israel Deaconess Medical Center in Boston, MA. Her work is focused on helping researchers communicate their findings in an effort to translate novel analytical approaches and clinical expertise into improved outcomes for patients"}]},{"given":"Tianyi","family":"Zang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology at Harbin Institute of Technology (HIT), China. Before joining HIT in 2009, he was a research fellow at the Department of Computer Science at University of Oxford, UK. His current research is concerned with biomedical bigdata computing and algorithms, deep-learning algorithms for network data, intelligent recommendation algorithms, and modeling and analys"}]},{"given":"Jiajie","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Computer Science at Northwestern Polytechnical University. His expertise is computational biology and machine learning. Availability and implementation: https:\/\/github.com\/zty2009\/GCN-DNN\/"}]}],"member":"286","published-online":{"date-parts":[[2020,5,4]]},"reference":[{"key":"2021070817465103200_ref1","first-page":"211","article-title":"Interactive visual analysis of drug\u2013target interaction networks using drug target profiler, with applications to precision medicine and drug repurposing","volume":"21","author":"Tanoli","year":"2020","journal-title":"Brief Bioinform"},{"key":"2021070817465103200_ref2","doi-asserted-by":"crossref","first-page":"1232","DOI":"10.7150\/ijbs.24612","article-title":"Review of drug repositioning approaches and resources","volume":"14","author":"Xue","year":"2018","journal-title":"Int J Biol Sci"},{"key":"2021070817465103200_ref3","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1016\/j.drudis.2015.08.001","article-title":"Identifying compound efficacy targets in phenotypic drug discovery","volume":"21","author":"Schirle","year":"2016","journal-title":"Drug 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