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.
Kloosterman, A. M., Cimermancic, P., Elsayed, S. S., Du, C., Hadjithomas, M., Donia, M. S., Fischbach, M. A., van Wezel, G. P. & Medema, M. H., 22 Dec 2020, In: PloS Biology.18, e3001026.
Research output: Contribution to journal › Article › Academic › peer-review
Kloosterman, A. M. (Creator), Cimermancic, P. (Creator), Elsayed, S. S. (Creator), Du, C. (Creator), Hadjithomas, M. (Creator), Donia, M. S. (Creator), Van Wezel, G. P. (Creator), Medema, M. (Creator) (19 May 2020). decRiPPter datasets - Integration of machine learning and pan-genomics expands the biosynthetic landscape of RiPP natural products. Leiden University. 10.5281/zenodo.3834818