{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:10:04Z","timestamp":1783437004518,"version":"3.54.6"},"reference-count":26,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2024,4,6]],"date-time":"2024-04-06T00:00:00Z","timestamp":1712361600000},"content-version":"vor","delay-in-days":10,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["92370131"],"award-info":[{"award-number":["92370131"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,3,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>This special issue focuses on computational model for drug research regarding drug bioactivity prediction, drug-related interaction prediction, modelling for immunotherapy and modelling for treatment of a specific disease, as conveyed by the following six research and four review articles. Notably, these 10 papers described a wide variety of in-depth drug research from the computational perspective and may represent a snapshot of the wide research landscape.<\/jats:p>","DOI":"10.1093\/bib\/bbae158","type":"journal-article","created":{"date-parts":[[2024,4,6]],"date-time":"2024-04-06T14:11:15Z","timestamp":1712412675000},"source":"Crossref","is-referenced-by-count":8,"title":["Computational model for drug research"],"prefix":"10.1093","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9028-5342","authenticated-orcid":false,"given":"Xing","family":"Chen","sequence":"first","affiliation":[{"name":"School of Science, Jiangnan University , Wuxi, 214122 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Huang","sequence":"additional","affiliation":[{"name":"The Future Laboratory, Tsinghua University , Beijing, 100084 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,4,5]]},"reference":[{"key":"2024040614105330100_ref1","doi-asserted-by":"crossref","first-page":"701","DOI":"10.1038\/nrd2944","article-title":"Lowering industry firewalls: pre-competitive informatics initiatives in drug discovery","volume":"8","author":"Barnes","year":"2009","journal-title":"Nat Rev Drug Discov"},{"key":"2024040614105330100_ref2","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1146\/annurev-pharmtox-010919-023324","article-title":"Big data and artificial intelligence modeling for drug discovery","volume":"60","author":"Zhu","year":"2020","journal-title":"Annu Rev Pharmacol Toxicol"},{"key":"2024040614105330100_ref3","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/bs.pmch.2017.12.003","article-title":"Big data in drug discovery","volume":"57","author":"Brown","year":"2018","journal-title":"Prog Med Chem"},{"key":"2024040614105330100_ref4","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1038\/s42256-022-00463-x","article-title":"The transformational role of GPU computing and deep learning in drug discovery","volume":"4","author":"Pandey","year":"2022","journal-title":"Nat Mach Intell"},{"key":"2024040614105330100_ref5","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1080\/17460441.2018.1465407","article-title":"Advancing drug discovery via GPU-based deep learning","volume":"13","author":"Gawehn","year":"2018","journal-title":"Expert Opin Drug Discovery"},{"key":"2024040614105330100_ref6","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1038\/s41573-020-00117-w","article-title":"Image-based profiling for drug discovery: Due for a machine-learning upgrade?","volume":"20","author":"Chandrasekaran","year":"2021","journal-title":"Nat Rev Drug Discov"},{"key":"2024040614105330100_ref7","doi-asserted-by":"crossref","first-page":"2017","DOI":"10.1016\/j.drudis.2019.07.006","article-title":"Deep learning in drug discovery: opportunities, challenges and future prospects","volume":"24","author":"Lavecchia","year":"2019","journal-title":"Drug Discov Today"},{"key":"2024040614105330100_ref8","doi-asserted-by":"crossref","first-page":"592","DOI":"10.1016\/j.tips.2019.06.004","article-title":"Advancing drug discovery via artificial intelligence","volume":"40","author":"Chan","year":"2019","journal-title":"Trends Pharmacol Sci"},{"key":"2024040614105330100_ref9","doi-asserted-by":"crossref","first-page":"1241","DOI":"10.1016\/j.drudis.2018.01.039","article-title":"The rise of deep learning in drug discovery","volume":"23","author":"Chen","year":"2018","journal-title":"Drug Discov Today"},{"key":"2024040614105330100_ref10","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1038\/s41573-019-0024-5","article-title":"Applications of machine learning in drug discovery and development","volume":"18","author":"Vamathevan","year":"2019","journal-title":"Nat Rev Drug Discov"},{"key":"2024040614105330100_ref11","doi-asserted-by":"crossref","first-page":"1131","DOI":"10.1038\/aps.2012.109","article-title":"Computational drug discovery","volume":"33","author":"Ou-Yang","year":"2012","journal-title":"Acta Pharmacol Sin"},{"key":"2024040614105330100_ref12","doi-asserted-by":"crossref","first-page":"1773","DOI":"10.1038\/s41591-022-01981-2","article-title":"Multimodal biomedical AI","volume":"28","author":"Acosta","year":"2022","journal-title":"Nat Med"},{"key":"2024040614105330100_ref13","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.drudis.2020.10.010","article-title":"Artificial intelligence in drug discovery and development","volume":"26","author":"Paul","year":"2021","journal-title":"Drug Discov Today"},{"key":"2024040614105330100_ref14","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1080\/17460441.2022.1985108","article-title":"Success stories of AI in drug discovery-Where do things stand?","volume":"17","author":"Mak","year":"2022","journal-title":"Expert Opin Drug Discovery"},{"key":"2024040614105330100_ref15","doi-asserted-by":"crossref","first-page":"899","DOI":"10.1038\/s41573-022-00472-w","article-title":"Phenotypic drug discovery: recent successes, lessons learned and new directions","volume":"21","author":"Vincent","year":"2022","journal-title":"Nat Rev Drug Discov"},{"key":"2024040614105330100_ref16","doi-asserted-by":"crossref","first-page":"127","DOI":"10.2174\/156802610790232251","article-title":"Successful applications of computer aided drug discovery: moving drugs from concept to the clinic","volume":"10","author":"Talele","year":"2010","journal-title":"Curr Top Med Chem"},{"key":"2024040614105330100_ref17","doi-asserted-by":"crossref","first-page":"bbac077","DOI":"10.1093\/bib\/bbac077","article-title":"AFSE: towards improving model generalization of deep graph learning of ligand bioactivities targeting GPCR proteins","volume":"23","author":"Yin","year":"2022","journal-title":"Brief Bioinform"},{"key":"2024040614105330100_ref18","doi-asserted-by":"crossref","first-page":"bbac160","DOI":"10.1093\/bib\/bbac160","article-title":"Biological activities of drug inactive ingredients","volume":"23","author":"Zhang","year":"2022","journal-title":"Brief Bioinform"},{"key":"2024040614105330100_ref19","doi-asserted-by":"crossref","first-page":"bbac080","DOI":"10.1093\/bib\/bbac080","article-title":"Review on predicting pairwise relationships between human microbes, drugs and diseases: from biological data to computational models","volume":"23","author":"Wang","year":"2022","journal-title":"Brief Bioinform"},{"key":"2024040614105330100_ref20","doi-asserted-by":"crossref","first-page":"bbac151","DOI":"10.1093\/bib\/bbac151","article-title":"Directed graph attention networks for predicting asymmetric drug\u2013drug interactions","volume":"23","author":"Feng","year":"2022","journal-title":"Brief Bioinform"},{"key":"2024040614105330100_ref21","doi-asserted-by":"crossref","first-page":"bbac228","DOI":"10.1093\/bib\/bbac228","article-title":"DSEATM: drug set enrichment analysis uncovering disease mechanisms by biomedical text mining","volume":"23","author":"Luo","year":"2022","journal-title":"Brief Bioinform"},{"key":"2024040614105330100_ref22","doi-asserted-by":"crossref","first-page":"bbac229","DOI":"10.1093\/bib\/bbac229","article-title":"Network approaches for modeling the effect of drugs and diseases","volume":"23","author":"Rintala","year":"2022","journal-title":"Brief Bioinform"},{"key":"2024040614105330100_ref23","doi-asserted-by":"crossref","first-page":"bbac076","DOI":"10.1093\/bib\/bbac076","article-title":"HLA3D: an integrated structure-based computational toolkit for immunotherapy","volume":"23","author":"Li","year":"2022","journal-title":"Brief Bioinform"},{"key":"2024040614105330100_ref24","doi-asserted-by":"crossref","first-page":"bbac267","DOI":"10.1093\/bib\/bbac267","article-title":"Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery","volume":"23","author":"Wilman","year":"2022","journal-title":"Brief Bioinform"},{"key":"2024040614105330100_ref25","doi-asserted-by":"crossref","first-page":"bbac198","DOI":"10.1093\/bib\/bbac198","article-title":"Computational methods to assist in the discovery of pharmacological chaperones for rare diseases","volume":"23","author":"Scafuri","year":"2022","journal-title":"Brief Bioinform"},{"key":"2024040614105330100_ref26","doi-asserted-by":"crossref","first-page":"bbac332","DOI":"10.1093\/bib\/bbac332","article-title":"Scoring personalized molecular portraits identify systemic lupus erythematosus subtypes and predict individualized drug responses, symptomatology and disease progression","volume":"23","author":"Toro-Dom\u00ednguez","year":"2022","journal-title":"Brief Bioinform"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/3\/bbae158\/57165993\/bbae158.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/25\/3\/bbae158\/57165993\/bbae158.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,6]],"date-time":"2024-04-06T14:11:27Z","timestamp":1712412687000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbae158\/7641198"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,27]]},"references-count":26,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2024,3,27]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbae158","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2024,5,1]]},"published":{"date-parts":[[2024,3,27]]},"article-number":"bbae158"}}