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README.md

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# Chemical Representation Learning for Toxicity Prediction
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PyTorch implementation related to the paper *Chemical Representation Learning for Toxicity Prediction* (Born et al, 2023, Under review at *Digital Discovery*).
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PyTorch implementation related to the paper *Chemical Representation Learning for Toxicity Prediction* ([Born et al, 2023, *Digital Discovery*](https://pubs.rsc.org/en/content/articlehtml/2023/dd/d2dd00099g)).
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## Training your own model
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The library itself has few dependencies (see [setup.py](setup.py)) with loose requirements.
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## Citation
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If you use this code in your projects, please (temporarily) cite the following (full paper in review):
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If you use this code in your projects, please cite the following:
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```bib
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@article{born2023chemical,
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title={Chemical representation learning for toxicity prediction},
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author={Born, Jannis and Markert, Greta and Janakarajan, Nikita and Kimber, Talia B. and Volkamer, Andrea and Rodriguez Martinez, Maria and Manica, Matteo},
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journal={Under review at Digital Discovery},
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year={2023}
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author = {Born, Jannis and Markert, Greta and Janakarajan, Nikita and Kimber, Talia B. and Volkamer, Andrea and Martínez, María Rodríguez and Manica, Matteo},
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title = {Chemical representation learning for toxicity prediction},
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journal = {Digital Discovery},
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year = {2023},
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pages = {-},
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publisher = {RSC},
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doi = {10.1039/D2DD00099G},
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url = {http://dx.doi.org/10.1039/D2DD00099G}
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}
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```

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