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Por AlQuraishi Laboratory / OpenFold contributors →
Trainable PyTorch implementation of the AlphaFold 2 approach. Training and inference have different resource needs; code and downloaded parameters have separate terms.
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Trainable PyTorch implementation of the AlphaFold 2 approach. Training and inference have different resource needs; code and downloaded parameters have separate terms.
Información cotejada con una fuente oficial; no es un ensayo experimental directo. Fuente · Última revisión: 16/09/2026, 17:33:40 UTC
Use this citation format when referencing OpenFold in scientific publications and benchmark papers.
@software{openfold_2026,
title = {{OpenFold}},
author = {{AlQuraishi Laboratory / OpenFold contributors}},
year = {2026},
url = {https://github.com/aqlaboratory/openfold},
note = {Indexed on aibioatlas - AI for Biology and Drug Discovery}
}Live scientific citations queried from Europe PMC and PubMed for OpenFold.
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OpenFold Scientific Architecture · Credit: AlQuraishi Laboratory / OpenFold contributors · Open original ↗
Research and editorial use Source & attribution ↗ License ↗
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OpenFold Consortium Publishes Trainable PyTorch AlphaFold2 and Complex Benchmarks
1 Apr 2026
See project access and maintenance status
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