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README.md
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license: apache-2.0
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task_categories:
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- graph-ml
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[](https://doi.org/10.1093/bioinformatics/btaf408)
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[](https://arxiv.org/abs/2507.14468)
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##
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This dataset contains the benchmark data used in the paper **"BioGraphFusion: Graph Knowledge Embedding for Biological Completion and Reasoning"** published in *Bioinformatics*.
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##
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The dataset includes three biomedical knowledge graph completion tasks with background knowledge integration:
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- **Main Dataset**: UMLS (2,523 triples) with multi-domain entities
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- **Description**: Reasons about medical concepts and their hierarchical relationships
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##
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| Dataset | Task | Background Knowledge Sources | Main Dataset Targets | Total Triples |
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|---------|------|------------------------------|---------------------|---------------|
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| **Protein-Chemical Interaction** | Protein-chemical interaction prediction | Drug-Disease Relationships SIDER (14,631) + Disease-Gene Relationships DisGeNet (130,820) | STITCH (23,074) Chemical | ~168K |
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| **Medical Ontology Reasoning** | Medical concept reasoning | Various Medical Relationships UMLS (4,006) | UMLS (2,523) Multi-domain Entities | ~6.5K |
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##
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### Loading the Dataset
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umls_data = load_dataset("Y-TARL/BioGraphFusion", "umls")
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```
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##
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If you use this dataset in your research, please cite our paper:
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}
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```
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- **Paper**: [Bioinformatics](https://doi.org/10.1093/bioinformatics/btaf408)
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- **Preprint**: [arXiv:2507.14468](https://arxiv.org/abs/2507.14468)
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- **Code**: [GitHub Repository](https://github.com/Y-TARL/BioGraphFusion)
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##
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This dataset is released under the Apache 2.0 License.
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##
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We thank the original data providers:
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- STITCH for protein-chemical interactions
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- UMLS for medical ontology data
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##
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For questions about the dataset, please open an issue in the [GitHub repository](https://github.com/Y-TARL/BioGraphFusion/issues).
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๏ปฟ---
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license: apache-2.0
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task_categories:
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- graph-ml
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[](https://doi.org/10.1093/bioinformatics/btaf408)
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[](https://arxiv.org/abs/2507.14468)
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## ๐ Dataset Description
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This dataset contains the benchmark data used in the paper **"BioGraphFusion: Graph Knowledge Embedding for Biological Completion and Reasoning"** published in *Bioinformatics*.
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## ๐๏ธ Dataset Structure
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The dataset includes three biomedical knowledge graph completion tasks with background knowledge integration:
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- **Main Dataset**: UMLS (2,523 triples) with multi-domain entities
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- **Description**: Reasons about medical concepts and their hierarchical relationships
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## ๐ Dataset Statistics
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| Dataset | Task | Background Knowledge Sources | Main Dataset Targets | Total Triples |
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|---------|------|------------------------------|---------------------|---------------|
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| **Protein-Chemical Interaction** | Protein-chemical interaction prediction | Drug-Disease Relationships SIDER (14,631) + Disease-Gene Relationships DisGeNet (130,820) | STITCH (23,074) Chemical | ~168K |
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| **Medical Ontology Reasoning** | Medical concept reasoning | Various Medical Relationships UMLS (4,006) | UMLS (2,523) Multi-domain Entities | ~6.5K |
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## ๐ป Usage
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### Loading the Dataset
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umls_data = load_dataset("Y-TARL/BioGraphFusion", "umls")
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```
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## ๐ Citation
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If you use this dataset in your research, please cite our paper:
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}
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```
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## ๐ Related Resources
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- **Paper**: [Bioinformatics](https://doi.org/10.1093/bioinformatics/btaf408)
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- **Preprint**: [arXiv:2507.14468](https://arxiv.org/abs/2507.14468)
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- **Code**: [GitHub Repository](https://github.com/Y-TARL/BioGraphFusion)
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## ๐ License
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This dataset is released under the Apache 2.0 License.
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## ๐ Acknowledgements
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We thank the original data providers:
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- STITCH for protein-chemical interactions
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- UMLS for medical ontology data
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## ๐ Contact
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For questions about the dataset, please open an issue in the [GitHub repository](https://github.com/Y-TARL/BioGraphFusion/issues).
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