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Download THIRD_PARTY_DATA.md from GENTEL-Lab/E3former_data: direct link, hf CLI and curl.
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https://huggingface.co/datasets/GENTEL-Lab/E3former_data/resolve/main/THIRD_PARTY_DATA.md
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curl -L -o THIRD_PARTY_DATA.md https://huggingface.co/datasets/GENTEL-Lab/E3former_data/resolve/main/THIRD_PARTY_DATA.md
1.3 kB
| # Data Sources and Attribution | |
| This release packages processed protein objects, labels, and split lists for | |
| E3former. Source data retain their original notices and license terms. | |
| Our packaging and documentation are licensed under [CC BY 4.0](LICENSE). | |
| | Component | Source | Upstream license | | |
| |---|---|---| | |
| | CATH classification | [CATH](https://www.cathdb.info/wiki/doku/?id=start) | [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) | | |
| | PPBS labels and evaluation subsets | [ScanNet](https://github.com/jertubiana/ScanNet/tree/main/datasets/PPBS) | [Apache 2.0](licenses/ScanNet-APACHE-2.0.txt) | | |
| The upstream ScanNet license is retained unchanged. The processed objects in | |
| this release were prepared for the E3former data loader; they are not the | |
| original ScanNet distribution. | |
| ScanNet reference: Tubiana, J., Schneidman-Duhovny, D., and Wolfson, H. J. | |
| ScanNet: an interpretable geometric deep learning model for structure-based | |
| protein binding site prediction. Nature Methods 19, 730-739 (2022). | |
| https://doi.org/10.1038/s41592-022-01490-7 | |
| AlphaFold reference: Jumper, J. et al. Highly accurate protein structure | |
| prediction with AlphaFold. Nature 596, 583-589 (2021). | |
| https://doi.org/10.1038/s41586-021-03819-2 | |
| The E3former code license does not replace upstream dataset licenses. | |