Trust, but Verify II: A Practical Guide to Chemogenomics Data Curation.

Trust, but Verify II: A Practical Guide to Chemogenomics Data Curation.
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DOI:
10.1021/acs.jcim.6b00129
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发表时间:
2016-07-25
影响因子:
5.6
通讯作者:
Tropsha A
Tropsha A
中科院分区:
化学2区
文献类型:
--
作者:
Fourches D;Muratov E;Tropsha A

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越来越多的公众关注同行评审的科学文献中发表的实验数据缺乏可重复性。在此,我们回顾了有关实验数据质量的最新警报,并讨论了迄今为止为解决这一问题而采取的措施,特别是在化学基因组学领域。除了承认这个问题之外,我们还提出了一个化学和生物数据管理工作流程,该工作流程依赖于现有的化学信息学方法来标记,并在适当的时候纠正大型化学基因组学数据集中可能存在的错误条目。我们认为,坚持数据策展的最佳实践对于生成原始数据并将其存款化学基因组学数据库的实验科学家和依赖这些数据进行模型开发的计算研究人员都很重要。
There is a growing public concern about the lack of reproducibility of experimental data published in peer-reviewed scientific literature. Herein, we review the most recent alerts regarding experimental data quality and discuss initiatives taken thus far to address this problem, especially in the area of chemical genomics. Going beyond just acknowledging the issue, we propose a chemical and biological data curation workflow that relies on existing cheminformatics approaches to flag, and, when appropriate, correct possibly erroneous entries in large chemogenomics datasets. We posit that the adherence to the best practices for data curation is important for both experimental scientists who generate primary data and deposit them in chemical genomics databases and computational researchers who rely on these data for model development.
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