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  • 标题:A large-scale dataset of in vivo pharmacology assay results
  • 本地全文:下载
  • 作者:Fiona M. I. Hunter ; Francis L. Atkinson ; A. Patrícia Bento
  • 期刊名称:Scientific Data
  • 电子版ISSN:2052-4463
  • 出版年度:2018
  • 卷号:5
  • DOI:10.1038/sdata.2018.230
  • 语种:English
  • 出版社:Nature Publishing Group
  • 摘要: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.
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