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A large-scale dataset of in vivo pharmacology assay results
ChEMBL is a large-scale, open-access drug discovery resource containing bioactivity information primarily extracted from scientific literature. A substantial dataset of more than 135,000 in vivo assays has been collated as a key resource of animal models for translational medicine within drug discov...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6206617/ https://www.ncbi.nlm.nih.gov/pubmed/30351302 http://dx.doi.org/10.1038/sdata.2018.230 |
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author | Hunter, Fiona M. I. L. Atkinson, Francis Bento, A. Patrícia Bosc, Nicolas Gaulton, Anna Hersey, Anne Leach, Andrew R. |
author_facet | Hunter, Fiona M. I. L. Atkinson, Francis Bento, A. Patrícia Bosc, Nicolas Gaulton, Anna Hersey, Anne Leach, Andrew R. |
author_sort | Hunter, Fiona M. I. |
collection | PubMed |
description | ChEMBL is a large-scale, open-access drug discovery resource containing bioactivity information primarily extracted from scientific literature. A substantial dataset of more than 135,000 in vivo assays has been collated as a key resource of animal models for translational medicine within drug discovery. To improve the utility of the in vivo data, an extensive data curation task has been undertaken that allows the assays to be grouped by animal disease model or phenotypic endpoint. The dataset contains previously unavailable information about compounds or drugs tested in animal models and, in conjunction with assay data on protein targets or cell- or tissue- based systems, allows the investigation of the effects of compounds at differing levels of biological complexity. Equally, it enables researchers to identify compounds that have been investigated for a group of disease-, pharmacology- or toxicity-relevant assays. |
format | Online Article Text |
id | pubmed-6206617 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-62066172018-11-06 A large-scale dataset of in vivo pharmacology assay results Hunter, Fiona M. I. L. Atkinson, Francis Bento, A. Patrícia Bosc, Nicolas Gaulton, Anna Hersey, Anne Leach, Andrew R. Sci Data Data Descriptor ChEMBL is a large-scale, open-access drug discovery resource containing bioactivity information primarily extracted from scientific literature. A substantial dataset of more than 135,000 in vivo assays has been collated as a key resource of animal models for translational medicine within drug discovery. To improve the utility of the in vivo data, an extensive data curation task has been undertaken that allows the assays to be grouped by animal disease model or phenotypic endpoint. The dataset contains previously unavailable information about compounds or drugs tested in animal models and, in conjunction with assay data on protein targets or cell- or tissue- based systems, allows the investigation of the effects of compounds at differing levels of biological complexity. Equally, it enables researchers to identify compounds that have been investigated for a group of disease-, pharmacology- or toxicity-relevant assays. Nature Publishing Group 2018-10-23 /pmc/articles/PMC6206617/ /pubmed/30351302 http://dx.doi.org/10.1038/sdata.2018.230 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article. |
spellingShingle | Data Descriptor Hunter, Fiona M. I. L. Atkinson, Francis Bento, A. Patrícia Bosc, Nicolas Gaulton, Anna Hersey, Anne Leach, Andrew R. A large-scale dataset of in vivo pharmacology assay results |
title | A large-scale dataset of in vivo pharmacology assay results |
title_full | A large-scale dataset of in vivo pharmacology assay results |
title_fullStr | A large-scale dataset of in vivo pharmacology assay results |
title_full_unstemmed | A large-scale dataset of in vivo pharmacology assay results |
title_short | A large-scale dataset of in vivo pharmacology assay results |
title_sort | large-scale dataset of in vivo pharmacology assay results |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6206617/ https://www.ncbi.nlm.nih.gov/pubmed/30351302 http://dx.doi.org/10.1038/sdata.2018.230 |
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