E3former Datasets
Processed datasets for Energy-Adaptive Equivariant State Space Models for Noise-Robust Protein Structure Representation.
Datasets
| Dataset | Structure | Task | Train | Validation | Test |
|---|---|---|---|---|---|
| CATH | Experimental | Inverse folding | 18,009 | 607 | 1,119 |
| CATH-AF | AlphaFold-derived | Inverse folding | 16,467 | 559 | 1,015 |
| PPBS | Experimental | Binding-site prediction | 12,577 | 3,178 | 3,984 |
| PPBS-AF | AlphaFold-derived | Binding-site prediction | 11,345 | 2,876 | 3,636 |
The archives contain processed PyTorch/PyG protein objects and fixed train/validation/test splits. PPBS includes the 70, homology, topology, and none test subsets. Family-specific manifests record split counts and archive checksums.
Download
hf download GENTEL-Lab/E3former_data --repo-type dataset --local-dir e3former_data
Or, from the E3former code directory:
python scripts/download.py --namespace GENTEL-Lab
e3former check-data
To install one dataset, add --only cath, --only cath-af, --only ppbs, or
--only ppbs-af to the download command. The script verifies SHA256 and extracts
the archives into the matching data/ directories.
Use Python 3.10 and the dependencies pinned in the E3former installation. These are processed inputs for the provided data loader, not raw PDB files.
Sources
CATH uses CATH protein classifications and benchmark splits. PPBS labels and evaluation subsets originate from ScanNet. The AF variants provide AlphaFold-derived structures for the corresponding tasks. This release uses CC BY 4.0 for our contributions. Source materials retain their original licenses; see THIRD_PARTY_DATA.md.
Please cite E3former and the relevant source datasets when using this release.
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