biostudies-otherUnknown12Zainab Ashimiyu-AbdusalamJournal of cheminformatics35https://www.ebi.ac.uk/biostudies/studies/MODEL2407180002biostudies-other33431015Zainab Ashimiyu-AbdusalamfalseVoršilák2020 - Bayesian estimation of synthetic accessibility of organic compounds<p>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.</p><p><normal>Model Type:</normal> Predictive machine learning model.<br><normal>Model Relevance:</normal> Prediction of synthetic accessibility<br><normal>Model Encoded by:</normal> Miquel Duran-Frigola (Ersilia)<br><normal>Metadata Submitted in BioModels by:</normal> Zainab Ashimiyu-Abdusalam</p><p>Implementation of this model code by <a href="https://ersilia.io/">Ersilia</a> is available here: <br><a href="https://github.com/ersilia-os/eos7pw8">https://github.com/ersilia-os/eos7pw8</a></p><img src="https://www.ebi.ac.uk/biomodels/static-assets/images/ersilia-logo.png" alt="Ersilia Logo" width="150">2024-07-18T00:00:00Z2025-07-14T17:00:49.897Z2025-03-31T13:27:17.122ZMODEL2407180002STATO:0000274STATO:0000530STATO:0000233STATO:0000134STATO:0000415000230533431015NCIT:C53237NCIT:C16309NCIT:C142403C61408C45329C154407topic_3336topic_0154topic_3474CHEMINF:000316CHEMINF:000018MI:2225sybanonphereos7pw8