Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1230813 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:SYBA uses a fragment-based approach to classify whether a molecule is easy or hard to synthesize, and it can also be used to analyze the contribution of individual fragments to the total synthetic accessibility. The easy-to-synthesize dataset is an extract of the ZINC purchasable compounds, and the hard-to-synthesize dataset is generated using a Nonpher approach (introducing small molecular perturbations to transform molecules into more complex compounds). The fragments are calculated with ECFP8 descriptors, and independence between fragments is assumed.
Model Type: Predictive machine learning model.
Model Relevance: Prediction of synthetic accessibility
Model Encoded by: Miquel Duran-Frigola (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam
Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos7pw8
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