{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T05:42:13Z","timestamp":1768801333121,"version":"3.49.0"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2023,8,30]],"date-time":"2023-08-30T00:00:00Z","timestamp":1693353600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Scientific Research Program of Tianjin Education Commission","award":["2018KJ107"],"award-info":[{"award-number":["2018KJ107"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>A critical issue in drug benefit-risk assessment is to determine the frequency of side effects, which is performed by randomized controlled trails. Computationally predicted frequencies of drug side effects can be used to effectively guide the randomized controlled trails. However, it is more challenging to predict drug side effect frequencies, and thus only a few studies cope with this problem.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this work, we propose a neighborhood-regularization method (NRFSE) that leverages multiview data on drugs and side effects to predict the frequency of side effects. First, we adopt a class-weighted non-negative matrix factorization to decompose the drug\u2013side effect frequency matrix, in which Gaussian likelihood is used to model unknown drug\u2013side effect pairs. Second, we design a multiview neighborhood regularization to integrate three drug attributes and two side effect attributes, respectively, which makes most similar drugs and most similar side effects have similar latent signatures. The regularization can adaptively determine the weights of different attributes. We conduct extensive experiments on one benchmark dataset, and NRFSE improves the prediction performance compared with five state-of-the-art approaches. Independent test set of post-marketing side effects further validate the effectiveness of NRFSE.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>Source code and datasets are available at https:\/\/github.com\/linwang1982\/NRFSE or https:\/\/codeocean.com\/capsule\/4741497\/tree\/v1.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btad532","type":"journal-article","created":{"date-parts":[[2023,8,30]],"date-time":"2023-08-30T21:49:13Z","timestamp":1693432153000},"source":"Crossref","is-referenced-by-count":13,"title":["A neighborhood-regularization method leveraging multiview data for predicting the frequency of drug\u2013side effects"],"prefix":"10.1093","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5025-3880","authenticated-orcid":false,"given":"Lin","family":"Wang","sequence":"first","affiliation":[{"name":"College of Artificial Intelligence, Tianjin University of Science and Technology , No. 9, 13th Street, Tianjin Economic-Technological Development Area , Tianjin 300457, China"}]},{"given":"Chenhao","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Tianjin University of Science and Technology , No. 9, 13th Street, Tianjin Economic-Technological Development Area , Tianjin 300457, China"}]},{"given":"Xianyu","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Tianjin University of Science and Technology , No. 9, 13th Street, Tianjin Economic-Technological Development Area , Tianjin 300457, China"}]},{"given":"Jia","family":"Li","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence, Tianjin University of Science and Technology , No. 9, 13th Street, Tianjin Economic-Technological Development Area , Tianjin 300457, China"}]},{"given":"Wenjuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of General Education, Tianjin Foreign Studies University , No. 117, Machang Road, Hexi District , Tianjin 300204, China"}]}],"member":"286","published-online":{"date-parts":[[2023,8,30]]},"reference":[{"key":"2023090906503564900_btad532-B1","doi-asserted-by":"crossref","first-page":"803","DOI":"10.1517\/13543784.2013.794782","article-title":"Alprostadil infusion in patients with dry age related macular degeneration: a randomized controlled clinical trial","volume":"22","author":"Augustin","year":"2013","journal-title":"Expert Opin Investig Drugs"},{"key":"2023090906503564900_btad532-B2","doi-asserted-by":"crossref","first-page":"D907","DOI":"10.1093\/nar\/gku1066","article-title":"ADReCS: an ontology database for aiding standardization and hierarchical classification of adverse drug reaction terms","volume":"43","author":"Cai","year":"2015","journal-title":"Nucleic Acids 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