The confluence of big data and evolutionary genome mining for the discovery of natural products
Natural Product Reports, ISSN: 1460-4752, Vol: 38, Issue: 11, Page: 2024-2040
2021
- 30Citations
- 104Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations30
- Citation Indexes30
- CrossRef30
- 26
- Captures104
- Readers104
- 104
Review Description
This review covers literature between 2003-2021 The development and application of genome mining tools has given rise to ever-growing genetic and chemical databases and propelled natural products research into the modern age of Big Data. Likewise, an explosion of evolutionary studies has unveiled genetic patterns of natural products biosynthesis and function that support Darwin's theory of natural selection and other theories of adaptation and diversification. In this review, we aim to highlight how Big Data and evolutionary thinking converge in the study of natural products, and how this has led to an emerging sub-discipline of evolutionary genome mining of natural products. First, we outline general principles to best utilize Big Data in natural products research, addressing key considerations needed to provide evolutionary context. We then highlight successful examples where Big Data and evolutionary analyses have been combined to provide bioinformatic resources and tools for the discovery of novel natural products and their biosynthetic enzymes. Rather than an exhaustive list of evolution-driven discoveries, we highlight examples where Big Data and evolutionary thinking have been embraced for the evolutionary genome mining of natural products. After reviewing the nascent history of this sub-discipline, we discuss the challenges and opportunities of genomic and metabolomic tools with evolutionary foundations and/or implications and provide a future outlook for this emerging and exciting field of natural product research.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85119865040&origin=inward; http://dx.doi.org/10.1039/d1np00013f; http://www.ncbi.nlm.nih.gov/pubmed/34787598; https://xlink.rsc.org/?DOI=D1NP00013F; https://dx.doi.org/10.1039/d1np00013f; https://pubs.rsc.org/en/content/articlelanding/2021/np/d1np00013f
Royal Society of Chemistry (RSC)
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