<HashMap><database>biostudies-other</database><scores/><additional><omics_type>Unknown</omics_type><submitter>Zainab Ashimiyu-Abdusalam</submitter><journal>Advances in Neural Information Processing Systems 33 (NeurIPS 2020)</journal><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/MODEL2406050008</full_dataset_link><repository>biostudies-other</repository><additional_accession>10.48550/arXiv.2007.02835</additional_accession><pubmed_authors>Amna Ali</pubmed_authors><pubmed_authors>Zainab Ashimiyu-Abdusalam</pubmed_authors></additional><is_claimable>false</is_claimable><name>Rong2020 - Grover-bbbp: Prediction of the Blood-brain barrier penetration.</name><description>&lt;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.&lt;/p>&lt;p>&lt;normal>Model Type:&lt;/normal> Predicitive machine learning model.&lt;br>&lt;normal>Model Relevance:&lt;/normal> Predicts Probability that a molecule crosses the blood brain barrier.&lt;br>&lt;normal>Model Encoded by:&lt;/normal>  Amna Ali (Ersilia)&lt;br>&lt;normal>Metadata Submitted in BioModels by:&lt;/normal> Zainab Ashimiyu-Abdusalam&lt;/p>&lt;p>Implementation of this model code by &lt;a href="https://ersilia.io/">Ersilia&lt;/a> is available here: &lt;br>&lt;a href="https://github.com/ersilia-os/eos1amr">https://github.com/ersilia-os/eos1amr&lt;/a>&lt;/p>&lt;img src="https://www.ebi.ac.uk/biomodels/static-assets/images/ersilia-logo.png" alt="Ersilia Logo" width="150"></description><dates><release>2024-06-05T00:00:00Z</release><modification>2025-07-14T17:01:25.199Z</modification><creation>2025-03-31T13:26:51.014Z</creation></dates><accession>MODEL2406050008</accession><cross_references><ncit>C154407</ncit><doi>10.48550/arXiv.2007.02835</doi><unknown>eos1amr</unknown></cross_references></HashMap>