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decRiPPter datasets - Integration of machine learning and pan-genomics expands the biosynthetic landscape of RiPP natural products

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 19 May 2020Publisher:Zenodo
Authors: Kloosterman, Alexander M.; Cimermancic, Peter; Elsayed, Somayah S.; Du, Chao; Hadjithomas, Michalis; Donia, Mohamed S.; van Wezel, Gilles P.; +1 Authors

doi: 10.5281/zenodo.3834818 , 10.5281/zenodo.3834817

decRiPPter datasets - Integration of machine learning and pan-genomics expands the biosynthetic landscape of RiPP natural products

Abstract

Datasets for decRiPPter, a genome mining tool for novel types of ribosomally synthesized and post-translationally modified peptides (RiPPs). 1) All training data for the SVM and the scripts used to generate them, 2) The output from the analysis of 1,295 Streptomyces genomes, passed through the 'mild' and the 'strict' filter.

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Keywords

Natural products, genome mining, RiPP, decRiPPter, Biosynthetic gene cluster

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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impulse
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