{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T03:52:14Z","timestamp":1784433134648,"version":"3.55.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7]]},"abstract":"<jats:p>The identification of drug-target interactions (DTIs) is a key task in drug discovery, where drugs are chemical compounds and targets are proteins.\u00a0 Traditional DTI prediction methods are either time consuming (simulation-based methods) or heavily dependent on domain expertise (similarity-based and feature-based methods). In this work, we propose an end-to-end neural network model that predicts DTIs directly from low level representations.\u00a0 In addition to making predictions, our model provides biological interpretation using two-way attention mechanism. Instead of using simplified settings where a dataset is evaluated as a whole, we designed an evaluation dataset from BindingDB following more realistic settings where predictions of unobserved examples (proteins and drugs) have to be made.\u00a0 We experimentally compared our model with matrix factorization, similarity-based methods, and a previous deep learning approach.\u00a0 Overall, the results show that our model outperforms other approaches without requiring domain knowledge and feature engineering.\u00a0 In a case study, we illustrated the ability of our approach to provide biological insights to interpret the predictions.<\/jats:p>","DOI":"10.24963\/ijcai.2018\/468","type":"proceedings-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:49:10Z","timestamp":1530755350000},"page":"3371-3377","source":"Crossref","is-referenced-by-count":160,"title":["Interpretable Drug Target Prediction Using Deep Neural Representation"],"prefix":"10.24963","author":[{"given":"Kyle Yingkai","family":"Gao","sequence":"first","affiliation":[{"name":"IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Achille","family":"Fokoue","sequence":"additional","affiliation":[{"name":"IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heng","family":"Luo","sequence":"additional","affiliation":[{"name":"IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arun","family":"Iyengar","sequence":"additional","affiliation":[{"name":"IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sanjoy","family":"Dey","sequence":"additional","affiliation":[{"name":"IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Zhang","sequence":"additional","affiliation":[{"name":"IBM Research AI, 1101 Kitchawan Road, Yorktown Heights, NY 10598"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"10584","event":{"name":"Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}","theme":"Artificial Intelligence","location":"Stockholm, Sweden","acronym":"IJCAI-2018","number":"27","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2018,7,13]]},"end":{"date-parts":[[2018,7,19]]}},"container-title":["Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:53:07Z","timestamp":1530755587000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2018\/468"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2018\/468","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}