Benefiting from big data in natural products: importance of preserving foundational skills and prioritizing data quality.
Benefiting from big data in natural products: importance of preserving foundational skills and prioritizing data quality.
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DOI：
10.1039/d1np00061f
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发表时间：
2021-11-17
影响因子：
11.9
通讯作者：
Clardy J
中科院分区：
文献类型：
--
作者：
Cech NB;Medema MH;Clardy J
在基因组、新陈代谢和功能水平上的系统、大规模的研究已经改变了天然产品科学。技术的改进和获取光谱、色谱和基因组数据的成本的降低，再加上易于获取、经过精选和功能注释的数据集的创建，改变了几乎所有天然产品研究实验室的做法。人们期望天然产物研究人员致力于小分子的分离、纯化和结构阐明的日子已经一去不复返了。我们现在还参与分类、基因组、蛋白质组和/或代谢组收集的大数据，并使用这些数据来生成和测试假设。虽然人们常说在天然产品科学中使用大规模组学数据的目的是实现新药发现率的快速提高，但这还没有实现。与此同时，新技术为天然产品化学家提供了意想不到的机会，让他们提出和回答新的和不同的问题。带着这个观点，我们讨论了作为天然产品研究一部分的大数据的演变，并提供了几个例子，说明如何通过访问大数据来实现发现。我们还提请注意我们现有与大型数据集接触中的一些限制，并考虑克服这些限制所需的措施。大数据正在改变我们进行天然产品研究的方式，并创造出令人兴奋的新可能性。需要继续关注提高数据质量、增加访问和保留基本技能。
Systematic, large-scale, studies at the genomic, metabolomic, and functional level have transformed the natural product sciences. Improvements in technology and reduction in cost for obtaining spectroscopic, chromatographic, and genomic data coupled with the creation of readily accessible curated and functionally annotated data sets have altered the practices of virtually all natural product research laboratories. Gone are the days when the natural products researchers were expected to devote themselves exclusively to the isolation, purification, and structure elucidation of small molecules. We now also engage with big data in taxonomic, genomic, proteomic, and/or metabolomic collections, and use these data to generate and test hypotheses. While the oft stated aim for the use of large-scale -omics data in the natural products sciences is to achieve a rapid increase in the rate of discovery of new drugs, this has not yet come to pass. At the same time, new technologies have provided unexpected opportunities for natural products chemists to ask and answer new and different questions. With this viewpoint, we discuss the evolution of big data as a part of natural products research and provide a few examples of how discoveries have been enabled by access to big data. We also draw attention to some of the limitations in our existing engagement with large datasets and consider what would be necessary to overcome them. Big data is changing how we do natural products research and creating exciting new possibilities. Continued attention to enhancing data quality, increasing access, and preserving foundational skills is needed.
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影响因子：
15
作者：
Wu, Changsheng;Shang, Zhuo;Brady, Sean F.
通讯作者：
Brady, Sean F.
影响因子：
9.2
作者：
Kautsar SA;van der Hooft JJJ;de Ridder D;Medema MH
通讯作者：
Medema MH
影响因子：
7.4
作者：
Mahieu NG;Patti GJ
通讯作者：
Patti GJ
影响因子：
16.6
作者：
Tu, Youyou
通讯作者：
Tu, Youyou
影响因子：
15
作者：
WANI, MC;TAYLOR, HL;MCPHAIL, AT
通讯作者：
MCPHAIL, AT