{"database":"biostudies-other","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["Zainab Ashimiyu-Abdusalam"],"journal":["Advances in Neural Information Processing Systems 33 (NeurIPS 2020)"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/MODEL2406050008"],"repository":["biostudies-other"],"additional_accession":["10.48550/arXiv.2007.02835"],"pubmed_authors":["Amna Ali","Zainab Ashimiyu-Abdusalam"]},"is_claimable":false,"name":"Rong2020 - Grover-bbbp: Prediction of the Blood-brain barrier penetration.","description":"<p>This model predicts the Blood-Brain Barrier (BBB) penetration potential of small molecules using as training data the curated MoleculeNet benchmark containing 2000 experimental data points. It has been trained using the GROVER transformer.</p><p><normal>Model Type:</normal> Predicitive machine learning model.<br><normal>Model Relevance:</normal> Predicts Probability that a molecule crosses the blood brain barrier.<br><normal>Model Encoded by:</normal>  Amna Ali (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/eos1amr\">https://github.com/ersilia-os/eos1amr</a></p><img src=\"https://www.ebi.ac.uk/biomodels/static-assets/images/ersilia-logo.png\" alt=\"Ersilia Logo\" width=\"150\">","dates":{"release":"2024-06-05T00:00:00Z","modification":"2025-07-14T17:01:25.199Z","creation":"2025-03-31T13:26:51.014Z"},"accession":"MODEL2406050008","cross_references":{"ncit":["C154407"],"doi":["10.48550/arXiv.2007.02835"],"unknown":["eos1amr"]}}