{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T17:38:40Z","timestamp":1775324320676,"version":"3.50.1"},"reference-count":40,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2021,12,2]],"date-time":"2021-12-02T00:00:00Z","timestamp":1638403200000},"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":["12026601"],"award-info":[{"award-number":["12026601"]}],"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":["11631015"],"award-info":[{"award-number":["11631015"]}],"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":["U1611265"],"award-info":[{"award-number":["U1611265"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,2,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Drug repositioning that aims to find new indications for existing drugs has been an efficient strategy for drug discovery. In the scenario where we only have confirmed disease\u2013drug associations as positive pairs, a negative set of disease\u2013drug pairs is usually constructed from the unknown disease\u2013drug pairs in previous studies, where we do not know whether drugs and diseases can be associated, to train a model for disease\u2013drug association prediction (drug repositioning). Drugs and diseases in these negative pairs can potentially be associated, but most studies have ignored them.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We present a method, springD2A, to capture the uncertainty in the negative pairs, and to discriminate between positive and unknown pairs because the former are more reliable. In springD2A, we introduce a spring-like penalty for the loss of negative pairs, which is strong if they are too close in a unit sphere, but mild if they are at a moderate distance. We also design a sequential sampling in which the probability of an unknown disease\u2013drug pair sampled as negative is proportional to its score predicted as positive. Multiple models are learned during sequential sampling, and we adopt parameter- and feature-based ensemble schemes to boost performance. Experiments show springD2A is an effective tool for drug-repositioning.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>A python implementation of springD2A and datasets used in this study are available at https:\/\/github.com\/wangyuanhao\/springD2A.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab820","type":"journal-article","created":{"date-parts":[[2021,11,30]],"date-time":"2021-11-30T22:42:43Z","timestamp":1638312163000},"page":"1353-1360","source":"Crossref","is-referenced-by-count":2,"title":["springD2A: capturing uncertainty in disease\u2013drug association prediction with model integration"],"prefix":"10.1093","volume":"38","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5435-2680","authenticated-orcid":false,"given":"Weiwen","family":"Wang","sequence":"first","affiliation":[{"name":"Intelligent Data Center, School of Mathematics, Sun Yat-Sen University , Guangzhou 510000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2291-0083","authenticated-orcid":false,"given":"Xiwen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Intelligent Data Center, School of Mathematics, Sun Yat-Sen University , Guangzhou 510000, China"}]},{"given":"Dao-Qing","family":"Dai","sequence":"additional","affiliation":[{"name":"Intelligent Data Center, School of Mathematics, Sun Yat-Sen University , Guangzhou 510000, China"}]}],"member":"286","published-online":{"date-parts":[[2021,12,2]]},"reference":[{"key":"2023020108545911600_btab820-B2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000016","article-title":"Distributed optimization and statistical learning via the alternating direction method of multipliers","volume":"3","author":"Boyd","year":"2010","journal-title":"Found. 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