Published December 18, 2024
| Version v1
Dataset
Open
Best Model Parameters for T-ALPHA: A Hierarchical Transformer-Based Deep Neural Network for Protein-Ligand Binding Affinity Prediction With Uncertainty-Aware Self-Learning for Protein-Specific Alignment
Description
This archive contains the best-performing model parameters for T-ALPHA, a hierarchical transformer-based deep neural network designed for protein-ligand binding affinity prediction.
Usage:
These model parameters can be directly used for inference with the accompanying codebase available on GitHub.
Associated Resources:
- GitHub Repository: [Link to GitHub repo]
- Full Dataset and Processed Files: [Zenodo link to datasets]
For detailed instructions on how to use these parameters, please refer to the GitHub repository and the accompanying README file.
Files
Files
(92.2 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:2fbbe4648186e0e83c296d6a9d96bea0
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92.2 MB | Download |
Additional details
Software
- Repository URL
- https://github.com/gregory-kyro/T-ALPHA
- Programming language
- Python