{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T04:58:44Z","timestamp":1773809924843,"version":"3.50.1"},"reference-count":37,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2019,10,14]],"date-time":"2019-10-14T00:00:00Z","timestamp":1571011200000},"content-version":"vor","delay-in-days":286,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Medical Scientific Research Foundation of Guangdong Province of China","award":["A2017071"],"award-info":[{"award-number":["A2017071"]}]},{"name":"GDAS\u2019 Project of Science and Technology Development","award":["2019GDASYL-0402001"],"award-info":[{"award-number":["2019GDASYL-0402001"]}]},{"DOI":"10.13039\/501100001809","name":"National Science Foundation of China","doi-asserted-by":"publisher","award":["81703416"],"award-info":[{"award-number":["81703416"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Deep learning contributes significantly to researches in biological sciences and drug discovery. Previous studies suggested that deep learning techniques have shown superior performance to other machine learning algorithms in virtual screening, which is a critical step to accelerate the drug discovery. However, the application of deep learning techniques in drug discovery and chemical biology are hindered due to the data availability, data further processing and lacking of the user-friendly deep learning tools and interface. Therefore, we developed a user-friendly web server with integration of the state of art deep learning algorithm, which utilizes either the public or user-provided dataset to help biologists or chemists perform virtual screening either the chemical probes or drugs for a specific target of interest. With DeepScreening, user could conveniently construct a deep learning model and generate the target-focused de novo libraries. The constructed classification and regression models could be subsequently used for virtual screening against the generated de novo libraries, or diverse chemical libraries in stock. From deep models training to virtual screening, and target focused de novo library generation, all those tasks could be finished with DeepScreening. We believe this deep learning-based web server will benefit to both biologists and chemists for probes or drugs discovery.<\/jats:p>","DOI":"10.1093\/database\/baz104","type":"journal-article","created":{"date-parts":[[2019,8,17]],"date-time":"2019-08-17T19:12:11Z","timestamp":1566069131000},"source":"Crossref","is-referenced-by-count":75,"title":["DeepScreening: a deep learning-based screening web server for accelerating drug discovery"],"prefix":"10.1093","volume":"2019","author":[{"given":"Zhihong","family":"Liu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Guangdong Institute of Microbiology, Guangdong Academy of Sciences, 100 Xianlie Middle Road, Guangzhou 510070, China"}]},{"given":"Jiewen","family":"Du","sequence":"additional","affiliation":[{"name":"Division of Algorithm, Beijing Jingpai Technology Co., Ltd. 1500-1, Hailong Building Z-Park, Beijing 100090, China"}]},{"given":"Jiansong","family":"Fang","sequence":"additional","affiliation":[{"name":"Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, 9620 Carnegie Ave n building, Cleveland, OH 44106, USA"}]},{"given":"Yulong","family":"Yin","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Guangdong Institute of Microbiology, Guangdong Academy of Sciences, 100 Xianlie Middle Road, Guangzhou 510070, China"}]},{"given":"Guohuan","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Guangdong Institute of Microbiology, Guangdong Academy of Sciences, 100 Xianlie Middle Road, Guangzhou 510070, China"}]},{"given":"Liwei","family":"Xie","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Applied Microbiology Southern China, Guangdong Provincial Key Laboratory of Microbial Culture Collection and Application, Guangdong Open Laboratory of Applied Microbiology, Guangdong Institute of Microbiology, Guangdong Academy of Sciences, 100 Xianlie Middle Road, Guangzhou 510070, China"},{"name":"Zhujiang Hospital, Southern Medical University, 253 Industrial Avenue, Guangzhou 510282, China"}]}],"member":"286","published-online":{"date-parts":[[2019,10,11]]},"reference":[{"key":"2019101406085017000_ref1","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1038\/nmeth.3707","article-title":"Deep learning","volume":"13","author":"Rusk","year":"2015","journal-title":"Nat. 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