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  ---
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- license: apache-2.0
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- ---
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-
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-
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- ---
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-
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- ## 📄 `README.md` for **DDInter**
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-
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- ```markdown
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- ---
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  pretty_name: DDInter Inductive Reasoning
 
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  annotations_creators:
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  - no-annotation
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  language:
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  - en
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  task_categories:
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- - reasoning
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- - relation-classification
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- license: mit
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  ---
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- ### Dataset Summary
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-
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- DDInter provides drug-drug interaction data labeled with three severity levels (e.g., 'Major','Moderate' and 'Minor').
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- Each example includes descriptions for both drugs, interaction label, and multi-hop paths extracted from a biomedical knowledge graph (Hetionet).
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- This dataset supports research in biomedical relational inductive reasoning, DDI prediction, and path-based inference.
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- ### Columns
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- | Column | Description |
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- |--------|-------------|
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- | `drug1_db`, `drug2_db` | DrugBank IDs |
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- | `drug1_id`, `drug2_id` | Node IDs |
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- | `drug_pair` | Optional pair ID |
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- | `drug1_name`, `drug2_name` | Drug names |
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- | `drug1_desc`, `drug2_desc` | Descriptions of each drug |
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- | `label` | Interaction severity (e.g., Moderate) |
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- | `label_idx` | Numeric label |
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- | `all_paths`, `all_paths_str`, `path_str` | Paths from the knowledge graph |
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- ### Example
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  ```json
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  {
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  "path_str": "Mannitol (Compound) binds ABCB1 (Gene) and ABCG2 (Gene)..."
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  }
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- Use the pandas option to load the dataset
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
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  pretty_name: DDInter Inductive Reasoning
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+ license: apache-2.0
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  annotations_creators:
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  - no-annotation
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  language:
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  - en
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  task_categories:
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+ - question-answering
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+ - text-generation
 
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  ---
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+ # DDInter: Inductive Reasoning Dataset
 
 
 
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+ DDInter provides drug–drug interaction (DDI) data labeled with three severity levels (`Major`, `Moderate`, `Minor`). Each example includes drug descriptions, an interaction label, and multi-hop paths extracted from a biomedical knowledge graph (Hetionet).
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+ ## 💡 Columns
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+ | Column | Description |
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+ |---------------------|--------------------------------------------------|
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+ | `drug1_db`, `drug2_db` | DrugBank IDs |
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+ | `drug1_id`, `drug2_id` | Node IDs from the KG |
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+ | `drug_pair` | Optional drug pair identifier |
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+ | `drug1_name`, `drug2_name` | Names of each drug |
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+ | `drug1_desc`, `drug2_desc` | Descriptions of each drug |
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+ | `label` | Interaction severity (e.g., `Moderate`) |
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+ | `label_idx` | Numeric version of the label |
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+ | `all_paths`, `all_paths_str`, `path_str` | KG paths for reasoning |
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+ ## 📦 Example Record
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  ```json
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  {
 
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  "path_str": "Mannitol (Compound) binds ABCB1 (Gene) and ABCG2 (Gene)..."
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  }
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+ ## 📥 How to Load with pandas
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+
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+ ```python
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+ import pandas as pd
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+
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+ splits = {
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+ "train": "ddinter/train.json",
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+ "test": "ddinter/test.json"
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+ }
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+
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+ df = pd.read_json("hf://datasets/Tassy24/K-Paths-inductive-reasoning-ddinter/" + splits["train"], lines=True)
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+
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+
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+
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+ ---
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+
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+ ### 📜 **Citation (BibTeX)**
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+ ```markdown
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+ ## 📜 Citation
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+
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+ ```bibtex
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+ @article{abdullahi2025k,
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+ title={K-Paths: Reasoning over Graph Paths for Drug Repurposing and Drug Interaction Prediction},
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+ author={Abdullahi, Tassallah and Gemou, Ioanna and Nayak, Nihal V and Murtaza, Ghulam and Bach, Stephen H and Eickhoff, Carsten and Singh, Ritambhara},
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+ journal={arXiv preprint arXiv:2502.13344},
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+ year={2025}
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+ }