
This is a preservation copy of the Protein-Vec model by Hamasy et al 2023, originally published at: - https://www.biorxiv.org/content/10.1101/2023.11.26.568742v1 - https://github.com/tymor22/protein-vec This model was essential to our work Functional Protein Mining with Conformal Guarantees published in Nature Communications in 2025. As of 4 Feb 2026, the original download link is no longer accessible. We are re-uploading this model to ensure reproducibility of our published work. All credit for model development goes to the original authors. Please cite their original work: Learning sequence, structure, and function representations of proteins with language models Tymor Hamamsy, Meet Barot, James T. Morton, Martin Steinegger, Richard Bonneau, Kyunghyun Cho bioRxiv 2023.11.26.568742; doi: https://doi.org/10.1101/2023.11.26.568742 For questions about the model itself, please contact the original authors.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
