Francoeur2021 - SolTranNet–A Machine Learning Tool for Fast Aqueous Solubility Prediction
Ontology highlight
ABSTRACT: Fast aqueous solubility prediction based on the Molecule Attention Transformer (MAT). The authors used AqSolDB to fine-tune the MAT network to solubility prediction, achieving competitive scores in the Second Challenge to Predict Aqueous Solubility (SC2).
Model Type: Predictive machine learning model.
Model Relevance: Predicts log of the solubility of small molecules.
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/eos6oli
SUBMITTER:
Zainab Ashimiyu-Abdusalam
PROVIDER: MODEL2406030002 | BioModels | 2024-06-03
REPOSITORIES: BioModels
ACCESS DATA