MolTrans
A transformer-based model for predicting drug-target interactions using substructural pattern mining and augmented transformer encoders.
What is MolTrans?
MolTrans is a molecular interaction transformer model that predicts drug-target interactions using deep learning. It addresses key challenges in computational drug discovery by incorporating substructural pattern mining and leveraging unlabeled biomedical data to improve prediction accuracy and interpretability.
Bioinformatics researchers, computational chemists, and drug discovery scientists working on in-silico drug development who need accurate and interpretable drug-target interaction predictions.
MolTrans offers more accurate and interpretable predictions than existing methods by explicitly modeling substructural interactions and effectively utilizing both labeled and unlabeled molecular data through augmented transformer encoders.
Overview
MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction (Bioinformatics)
Use Cases
Best For
- Predicting drug-target interactions for drug discovery pipelines
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