Rong2020 - Grover-bbbp: Prediction of the Blood-brain barrier penetration.

ABSTRACT:

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.

Model Type: Predicitive machine learning model.
Model Relevance: Predicts Probability that a molecule crosses the blood brain barrier.
Model Encoded by: Amna Ali (Ersilia)
Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam

Implementation of this model code by Ersilia is available here:
https://github.com/ersilia-os/eos1amr

SUBMITTER: Zainab Ashimiyu-Abdusalam 

PROVIDER: MODEL2406050008 | biostudies-other |

SECONDARY ACCESSION(S): 10.48550/arXiv.2007.02835

REPOSITORIES: biostudies-other