{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T11:55:54Z","timestamp":1784548554288,"version":"3.55.0"},"reference-count":78,"publisher":"Oxford University Press (OUP)","issue":"D1","license":[{"start":{"date-parts":[[2022,11,18]],"date-time":"2022-11-18T00:00:00Z","timestamp":1668729600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62103436"],"award-info":[{"award-number":["62103436"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,1,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The toxic effects of compounds on environment, humans, and other organisms have been a major focus of many research areas, including drug discovery and ecological research. Identifying the potential toxicity in the early stage of compound\/drug discovery is critical. The rapid development of computational methods for evaluating various toxicity categories has increased the need for comprehensive and system-level collection of toxicological data, associated attributes, and benchmarks. To contribute toward this goal, we proposed TOXRIC (https:\/\/toxric.bioinforai.tech\/), a database with comprehensive toxicological data, standardized attribute data, practical benchmarks, informative visualization of molecular representations, and an intuitive function interface. The data stored in TOXRIC contains 113 372 compounds, 13 toxicity categories, 1474 toxicity endpoints covering in vivo\/in vitro endpoints\u00a0and 39 feature types, covering structural, target, transcriptome, metabolic data, and other descriptors. All the curated datasets of endpoints and features can be retrieved, downloaded and directly used as output or input to Machine Learning (ML)-based prediction models. In addition to serving as a data repository, TOXRIC also provides visualization of benchmarks and molecular representations for all endpoint datasets. Based on these results, researchers can better understand and select optimal feature types, molecular representations, and baseline algorithms for each endpoint prediction task. We believe that\u00a0the rich information on compound toxicology, ML-ready datasets, benchmarks\u00a0and molecular representation distribution can greatly facilitate toxicological investigations, interpretation of toxicological mechanisms, compound\/drug discovery\u00a0and the development of computational methods.<\/jats:p>","DOI":"10.1093\/nar\/gkac1074","type":"journal-article","created":{"date-parts":[[2022,11,19]],"date-time":"2022-11-19T02:25:46Z","timestamp":1668824746000},"page":"D1432-D1445","source":"Crossref","is-referenced-by-count":90,"title":["TOXRIC: a comprehensive database of toxicological data and benchmarks"],"prefix":"10.1093","volume":"51","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9611-4488","authenticated-orcid":false,"given":"Lianlian","family":"Wu","sequence":"first","affiliation":[{"name":"Department of Bioinformatics, Institute of Health Service and Transfusion Medicine , Beijing \u00a0100850, China"},{"name":"Academy of Medical Engineering and Translational Medicine, Tianjin University , Tianjin \u00a0300072, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bowei","family":"Yan","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics, Institute of Health Service and Transfusion Medicine , Beijing \u00a0100850, China"},{"name":"State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institute of Biomedical Sciences, Human Phenome Institute, Fudan University , Shanghai \u00a0200433, China"},{"name":"State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences , Beijing \u00a0102206, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junshan","family":"Han","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics, Institute of Health Service and Transfusion Medicine , Beijing \u00a0100850, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruijiang","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics, Institute of Health Service and Transfusion Medicine , Beijing \u00a0100850, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Xiao","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, Xiangya Hospital, Central South University , Changsha \u00a0410008, Hunan , China"},{"name":"Institute for Rational and Safe Medication Practices, National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University , Changsha \u00a0410008, Hunan , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4136-6151","authenticated-orcid":false,"given":"Song","family":"He","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics, Institute of Health Service and Transfusion Medicine , Beijing \u00a0100850, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1911-7922","authenticated-orcid":false,"given":"Xiaochen","family":"Bo","sequence":"additional","affiliation":[{"name":"Department of Bioinformatics, Institute of Health Service and Transfusion Medicine , Beijing \u00a0100850, China"},{"name":"Academy of Medical Engineering and Translational Medicine, Tianjin University , Tianjin \u00a0300072, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,11,18]]},"reference":[{"key":"2023010804331592900_B1","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1002\/wcms.1240","article-title":"In silico toxicology: computational methods for the prediction of chemical toxicity","volume":"6","author":"Raies","year":"2016","journal-title":"Wiley Interdiscip Rev. 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