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SkinSensDB: a curated database for skin sensitization assays
Skin sensitization is an important toxicological endpoint for chemical hazard determination and safety assessment. Prediction of chemical skin sensitizer had traditionally relied on data from rodent models. The development of the adverse outcome pathway (AOP) and associated alternative in vitro assa...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5285290/ https://www.ncbi.nlm.nih.gov/pubmed/28194231 http://dx.doi.org/10.1186/s13321-017-0194-2 |
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author | Wang, Chia-Chi Lin, Ying-Chi Wang, Shan-Shan Shih, Chieh Lin, Yi-Hui Tung, Chun-Wei |
author_facet | Wang, Chia-Chi Lin, Ying-Chi Wang, Shan-Shan Shih, Chieh Lin, Yi-Hui Tung, Chun-Wei |
author_sort | Wang, Chia-Chi |
collection | PubMed |
description | Skin sensitization is an important toxicological endpoint for chemical hazard determination and safety assessment. Prediction of chemical skin sensitizer had traditionally relied on data from rodent models. The development of the adverse outcome pathway (AOP) and associated alternative in vitro assays have reshaped the assessment of skin sensitizers. The integration of multiple assays as key events in the AOP has been shown to have improved prediction performance. Current computational models to predict skin sensitization mainly based on in vivo assays without incorporating alternative in vitro assays. However, there are few freely available databases integrating both the in vivo and the in vitro skin sensitization assays for development of AOP-based skin sensitization prediction models. To facilitate the development of AOP-based prediction models, a skin sensitization database named SkinSensDB has been constructed by curating data from published AOP-related assays. In addition to providing datasets for developing computational models, SkinSensDB is equipped with browsing and search tools which enable the assessment of new compounds for their skin sensitization potentials based on data from structurally similar compounds. SkinSensDB is publicly available at http://cwtung.kmu.edu.tw/skinsensdb. |
format | Online Article Text |
id | pubmed-5285290 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-52852902017-02-13 SkinSensDB: a curated database for skin sensitization assays Wang, Chia-Chi Lin, Ying-Chi Wang, Shan-Shan Shih, Chieh Lin, Yi-Hui Tung, Chun-Wei J Cheminform Database Skin sensitization is an important toxicological endpoint for chemical hazard determination and safety assessment. Prediction of chemical skin sensitizer had traditionally relied on data from rodent models. The development of the adverse outcome pathway (AOP) and associated alternative in vitro assays have reshaped the assessment of skin sensitizers. The integration of multiple assays as key events in the AOP has been shown to have improved prediction performance. Current computational models to predict skin sensitization mainly based on in vivo assays without incorporating alternative in vitro assays. However, there are few freely available databases integrating both the in vivo and the in vitro skin sensitization assays for development of AOP-based skin sensitization prediction models. To facilitate the development of AOP-based prediction models, a skin sensitization database named SkinSensDB has been constructed by curating data from published AOP-related assays. In addition to providing datasets for developing computational models, SkinSensDB is equipped with browsing and search tools which enable the assessment of new compounds for their skin sensitization potentials based on data from structurally similar compounds. SkinSensDB is publicly available at http://cwtung.kmu.edu.tw/skinsensdb. Springer International Publishing 2017-01-31 /pmc/articles/PMC5285290/ /pubmed/28194231 http://dx.doi.org/10.1186/s13321-017-0194-2 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Database Wang, Chia-Chi Lin, Ying-Chi Wang, Shan-Shan Shih, Chieh Lin, Yi-Hui Tung, Chun-Wei SkinSensDB: a curated database for skin sensitization assays |
title | SkinSensDB: a curated database for skin sensitization assays |
title_full | SkinSensDB: a curated database for skin sensitization assays |
title_fullStr | SkinSensDB: a curated database for skin sensitization assays |
title_full_unstemmed | SkinSensDB: a curated database for skin sensitization assays |
title_short | SkinSensDB: a curated database for skin sensitization assays |
title_sort | skinsensdb: a curated database for skin sensitization assays |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5285290/ https://www.ncbi.nlm.nih.gov/pubmed/28194231 http://dx.doi.org/10.1186/s13321-017-0194-2 |
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