Journal article Open Access
decRiPPter datasets - Integration of machine learning and pan-genomics expands the biosynthetic landscape of RiPP natural products
Kloosterman, Alexander M.;
Cimermancic, Peter;
Elsayed, Somayah S.;
Du, Chao;
Hadjithomas, Michalis;
Donia, Mohamed S.;
van Wezel, Gilles P.;
Medema, Marnix H.
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.
Files
(917.0 MB)
| Name | Size | |
|---|---|---|
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decRiPPter_Streptomyces.zip
md5:d206addc08fc075065b50b57dd645847 |
871.9 MB | Download |
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decRiPPter_SVM_training_data.zip
md5:9c441d9bc568011d792d799ba65d855a |
45.1 MB | Download |
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| Data volume | 26.6 GB | 26.6 GB |
| Unique views | 213 | 213 |
| Unique downloads | 40 | 40 |
Indexed in
- Publication date:
- May 19, 2020
- DOI:
-
- Keyword(s):
- RiPP decRiPPter genome mining Biosynthetic gene cluster Natural products
- License (for files):
- Creative Commons Attribution 4.0 International