{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T20:17:39Z","timestamp":1740169059399,"version":"3.37.3"},"reference-count":59,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2018YFA0701700","2021YFE0203700"],"award-info":[{"award-number":["2018YFA0701700","2021YFE0203700"]}]},{"name":"Postgraduate Research &amp; Practice Innovation Program of Jiangsu Province","award":["SJCX22_1106"],"award-info":[{"award-number":["SJCX22_1106"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U21A20521","62271178"],"award-info":[{"award-number":["U21A20521","62271178"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Zhejiang Provincial Natural Science Foundation of China","award":["LR23F010002"],"award-info":[{"award-number":["LR23F010002"]}]},{"name":"Jiangsu Provincial Maternal and Child Health Research","award":["F202034"],"award-info":[{"award-number":["F202034"]}]},{"name":"Wuxi Health Commission Precision Medicine","award":["J202106"],"award-info":[{"award-number":["J202106"]}]},{"name":"Jiangsu Provincial Six Talent Peaks","award":["YY-124"],"award-info":[{"award-number":["YY-124"]}]},{"DOI":"10.13039\/501100015377","name":"Shanghai Key Laboratory of Molecular Imaging","doi-asserted-by":"publisher","award":["18DZ2260400"],"award-info":[{"award-number":["18DZ2260400"]}],"id":[{"id":"10.13039\/501100015377","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1109\/jbhi.2024.3416348","type":"journal-article","created":{"date-parts":[[2024,6,18]],"date-time":"2024-06-18T17:55:21Z","timestamp":1718733321000},"page":"7633-7646","source":"Crossref","is-referenced-by-count":0,"title":["Advancing the Boundary of Pre-Trained Models for Drug Discovery: Interpretable Fine-Tuning Empowered by Molecular Physicochemical Properties"],"prefix":"10.1109","volume":"28","author":[{"given":"Xiaoqing","family":"Lian","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-2903-7443","authenticated-orcid":false,"given":"Jie","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"}]},{"given":"Tianxu","family":"Lv","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"}]},{"given":"Xiaoyan","family":"Hong","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"}]},{"given":"Longzhen","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9115-0896","authenticated-orcid":false,"given":"Wei","family":"Chu","sequence":"additional","affiliation":[{"name":"Affiliated Huishan Hospital of Xinglin College, Nantong University, Wuxi, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2354-0232","authenticated-orcid":false,"given":"Jianming","family":"Ni","sequence":"additional","affiliation":[{"name":"Department of Nuclear Medicine, Jiangnan University Medical Center, Wuxi, Jiangsu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7671-518X","authenticated-orcid":false,"given":"Xiang","family":"Pan","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.22270\/jddt.v8i5.1894"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/wcms.1608"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.2786"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.drudis.2020.10.010"},{"key":"ref5","first-page":"1","article-title":"Strategies for pre-training graph neural networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Hu","year":"2020"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.34133\/research.0004"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-022-00557-6"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539426"},{"key":"ref9","first-page":"2790","article-title":"Parameter-efficient transfer learning for NLP","volume-title":"Int. Conf. Mach. Learn.","author":"Houlsby","year":"2019"},{"key":"ref10","first-page":"1","article-title":"UniAdapter: Unified parameter-efficient transfer learning for cross-modal modeling","author":"Lu","year":"2024","journal-title":"Proc. Int. Conf. Learn. Representations"},{"key":"ref11","first-page":"1","article-title":"Vision transformer adapter for dense predictions","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Chen","year":"2023"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-short.1"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.418"},{"key":"ref14","first-page":"1","article-title":"Lora: Low-rank adaptation of large language models","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Hu","year":"2022"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.395"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.2533\/chimia.2017.661"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-021-10058-4"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.eacl-main.39"},{"issue":"1","key":"ref20","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref21","first-page":"2814","article-title":"Understanding dropout","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"2","author":"Baldi","year":"2013"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.243"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-022-00580-7"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.127063"},{"article-title":"Are learned molecular representations ready for prime time","year":"2019","author":"Yang","key":"ref25"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1039\/C7SC02664A"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.3389\/fenvs.2015.00080"},{"issue":"8","key":"ref28","doi-asserted-by":"crossref","first-page":"1225","DOI":"10.1021\/acs.chemrestox.6b00135","article-title":"ToxCast chemical landscape: Paving the road to 21st century toxicology","volume":"29","author":"Richard","year":"2016","journal-title":"Chem. Res. Toxicol."},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1039\/C7SC02664A"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1021\/ci300124c"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.chembiol.2016.07.023"},{"issue":"D1","key":"ref32","doi-asserted-by":"crossref","first-page":"D1075","DOI":"10.1093\/nar\/gkv1075","article-title":"The sider database of drugs and side effects","volume":"44","author":"Kuhn","year":"2016","journal-title":"Nucleic acids Res."},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-89689-0_33"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1021\/ci034243x"},{"issue":"1","key":"ref35","first-page":"3","article-title":"Lipophilicitymethods of determination and its role in medicinal chemistry","volume":"70","author":"Rutkowska","year":"2013","journal-title":"Acta Poloniae Pharm."},{"issue":"7","key":"ref36","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1007\/s10822-014-9747-x","article-title":"Freesolv: A database of experimental and calculated hydration free energies, with input files","volume":"28","author":"Mobley","year":"2014","journal-title":"J. Comput.-aided Mol. Des."},{"key":"ref37","first-page":"9929","article-title":"Understanding contrastive representation learning through alignment and uniformity on the hypersphere","author":"Wang","year":"2020","journal-title":"Proc. 37th Int. Conf. Mach. Learn."},{"issue":"86","key":"ref38","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"issue":"1","key":"ref39","doi-asserted-by":"crossref","DOI":"10.1186\/s13321-019-0380-5","article-title":"A general approach for retrosynthetic molecular core analysis","volume":"11","author":"Naveja","year":"2019","journal-title":"J. Cheminformatics"},{"key":"ref40","first-page":"754","article-title":"An efficient approach for assessing hyperparameter importance","volume-title":"Proc. Int. Conf. Mach. Learn 2014.","author":"Hutter","year":"2014"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/0022-1902(61)80142-5"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1021\/ja01500a088"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1039\/cs9800900091"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1021\/ci00057a005"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1021\/ja0630285"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.4155\/tde.10.37"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.3390\/molecules24081505"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-12-384935-9.10006-9"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/S0196-9781(99)00127-8"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1021\/jm3009025"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21660"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1021\/acsptsci.0c00161"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1021\/acsnano.0c05975"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1021\/acsptsci.2c00049"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1021\/acsptsci.0c00106"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1021\/acsptsci.0c00108"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1016\/j.slasd.2021.12.005"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.3389\/fphar.2020.592737"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1021\/acsptsci.0c00112"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6221020\/10779505\/10561461.pdf?arnumber=10561461","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T01:57:36Z","timestamp":1733882256000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10561461\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12]]},"references-count":59,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2024.3416348","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"type":"print","value":"2168-2194"},{"type":"electronic","value":"2168-2208"}],"subject":[],"published":{"date-parts":[[2024,12]]}}}