README.md

metadata

dataset_info:
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      - name: text
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      - name: labels
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      - name: validation
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      - name: test
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      - name: held_out
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    download_size: 153375375
    dataset_size: 400902547
  - config_name: large
    features:
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      - name: labels
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      - name: validation
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      - name: held_out
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  - config_name: standard
    features:
      - name: text
        dtype: string
      - name: labels
        dtype: string
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      - name: validation
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      - name: test
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        num_examples: 5000
      - name: held_out
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        num_examples: 5670
    download_size: 165141561
    dataset_size: 417933628.00000006
configs:
  - config_name: clustered
    data_files:
      - split: train
        path: clustered/train-*
      - split: validation
        path: clustered/validation-*
      - split: test
        path: clustered/test-*
      - split: held_out
        path: clustered/held_out-*
  - config_name: large
    data_files:
      - split: train
        path: large/train-*
      - split: validation
        path: large/validation-*
      - split: test
        path: large/test-*
      - split: held_out
        path: large/held_out-*
  - config_name: standard
    data_files:
      - split: train
        path: standard/train-*
      - split: validation
        path: standard/validation-*
      - split: test
        path: standard/test-*
      - split: held_out
        path: standard/held_out-*
license: mit
task_categories:
  - text2text-generation
tags:
  - chemistry
  - medical
  - targetd-protein-degradation
  - protac

✂️ PROTAC-Splitter Dataset ✂️

This Hugging-Face dataset contains the data for training and evaluating the Tranformer-based PROTAC-Splitter model.

If you find this dataset useful or want to know more, please consider reading and citing the following work:

@article{Ribes2025PROTACSplitter,
  title   = {PROTAC‐Splitter: A Machine Learning Framework for Automated Identification of PROTAC Substructures},
  author  = {Stefano Ribes and Ranxuan Zhang and Télio Cropsal and Anders Källberg and Christian Tyrchan and Eva Nittinger and Rocío Mercado},
  journal = {ChemRxiv},
  year    = {2025},
  month   = {Jul},
  day     = {08},
  doi     = {10.26434/chemrxiv-2025-bn1nv},
  url     = {https://chemrxiv.org/engage/chemrxiv/article-details/686670983ba0887c33677fc8},
  license = {CC BY 4.0}
}

Additional information on the models and data can also be found at this Zenodo link: https://zenodo.org/records/15797310

GitHub Repository 📝

The code for training and evaluation the PROTAC-Splitter models can be found at: https://github.com/ribesstefano/PROTAC-Splitter