Deep learning driven biosynthetic pathways navigation for natural products with bionavi-np

HIGHLIGHTS

• who: Shuangjia Zheng from the Schoolsen University, Guangzhou, China have published the research: Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP, in the Journal: NATURE COMMUNICATIONS NATURE COMMUNICATIONS
• how: For a fair comparison the authors used the same building block library (extended library) containing 437 available precursor metabolites extracted from iML1515 model46 as used in RetroPathRL.

SUMMARY

The larger data set of 60 K natural product-like reactions is named USPTO_NPL (see Methods for more details). Training strategy USPTO_NPL BioChem (w/o chirality) BioChem BioChem + USPTO_NPL BioChem . . .

 



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