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---
license: gpl-3.0
tags:
- biology
pretty_name: ProtHGT Knowledge Graph Data & Pretrained Checkpoints
---
# ProtHGT Knowledge Graph Data & Pretrained Checkpoints
This repository provides the **knowledge graph (KG) `.pt` files** and **pretrained model checkpoints** used in **ProtHGT: Heterogeneous Graph Transformers for Automated Protein Function Prediction Using Biological Knowledge Graphs and Language Models**.
- **Code (training & prediction)**: https://github.com/HUBioDataLab/ProtHGT
---
## What’s Inside
### data/
PyTorch Geometric-compatible KG files:
- Full KG file (e.g., `prothgt-kg.pt`)
- Train/validation/test splits (e.g., `prothgt-*-graph.pt`)
- Alternative KG versions under `alternative_protein_embeddings/` (e.g., `esm2/`, `prott5/`), where the protein node features differ by embedding type.
**Available Files**
```
├── prothgt-kg.pt # The default full knowledge graph containing TAPE embeddings as the initial protein representations.
├── prothgt-train-graph.pt # Training set (80% of the default full KG).
├── prothgt-val-graph.pt # Validation set (10% of the default full KG).
├── prothgt-test-graph.pt # Test set (10% of the default full KG).
└── alternative_protein_embeddings/ # Contains alternative KGs with different protein representations.
├──apaac/
│ └── ...
├──esm2/
│ └── ...
└──prott5/
└── ...
```
### models/
Pretrained ProtHGT models (`.pt`). Models are provided:
- per GO sub-ontology (e.g., Molecular Function / Biological Process / Cellular Component)
- per protein embedding type (default vs `esm2` / `prott5` / etc.)
**Important:** Use a model checkpoint that matches the KG embedding variant you are using.
**Available Files**
```
├── prothgt-model-molecular-function.pt # Pretrained ProtHGT checkpoint for Molecular Function (default/TAPE-based KG).
├── prothgt-model-biological-process.pt # Pretrained ProtHGT checkpoint for Biological Process (default/TAPE-based KG).
├── prothgt-model-cellular-component.pt # Pretrained ProtHGT checkpoint for Cellular Component (default/TAPE-based KG).
└── alternative_protein_embeddings/ # Models trained with alternative protein representations.
├── esm2/
│ └── ...
└── prott5/
└── ...
```
---
### How to Use (Training & Prediction)
To train or run inference, follow the instructions in the GitHub repository: https://github.com/HUBioDataLab/ProtHGT
Key scripts:
- `train.py` — trains ProtHGT using the provided KG splits
- `predict.py` — runs inference using pretrained checkpoints
---
### Citation
Please refer to our preprint for more information. If you use the ProtHGT method or the datasets provided in this repository, please cite this paper:
Ulusoy, E., & Dogan, T. (2025). ProtHGT: Heterogeneous Graph Transformers for Automated Protein Function Prediction Using Biological Knowledge Graphs and Language Models (p. 2025.04.19.649272). bioRxiv. [Link](https://doi.org/10.1101/2025.04.19.649272)
---
### Licensing
Copyright (C) 2025 HUBioDataLab
This dataset is released under GPL-3.0. |