--- 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.