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Reference change · event page

Reference changes · DOI

Doherty, Nathan Price, Daniel Bellieny-Rabelo, Yong K

Published notice on a work cited in the Pith corpus. Exact quotes below. No model judges whether any citation was load-bearing.

This page records that a citing paper's bibliography includes a work with a published notice. It is not a judgment on the citing paper.

Correction Crossref 1 open · 1 total · 0 disputed
DOI
10.1038/s41586-024-07809-y
Notice DOI
10.1038/s41586-024-08068-7
Event date
2024-09-24
Machine twin
JSON

01One-hop citing occurrences

Correction Open
Resilient Biosecurity in the Era of AI-Enabled Bioweapons

ref [46] · 2509.02610 · notice #8527 · dispute

Raw extraction · citation context

doi: https://doi.org/10.1016/j.ymthe.2025.04.003. URL https://www.sciencedirect.com/science/article/ pii/S1525001625002771. [46] Jason Nomburg, Erin E. Doherty, Nathan Price, Daniel Bellieny-Rabelo, Yong K. Zhu, and Jennifer A. Doudna. Birth of protein folds and functions in the virome. Nature, 633(8030):710-717, September 2024. ISSN 1476-4687. doi: 10.1038/s41586-024-07809-y. URL https://www.nature.com/articles/s41586-024-07809-y . Publisher: Nature Publishing Group. [47] Tao Huang and Yixue Li. Current progress, challenges, and future perspectives of language models for protein representation and protein design. The Innovation , 4(4):100446, 2023. ISSN 2666-6758. doi: https://doi.org/10.1016/j.xinn.2023.100446. URL https://www.

Parser render (TeX stripped for reading; raw above is the evidence)

doi: https://doi.org/10.1016/j.ymthe.2025.04.003. URL https://www.sciencedirect.com/science/article/ pii/S1525001625002771. [46] Jason Nomburg, Erin E. Doherty, Nathan Price, Daniel Bellieny-Rabelo, Yong K. Zhu, and Jennifer A. Doudna. Birth of protein folds and functions in the virome. Nature, 633(8030):710-717, September 2024. ISSN 1476-4687. doi: 10.1038/s41586-024-07809-y. URL https://www.nature.com/articles/s41586-024-07809-y . Publisher: Nature Publishing Group. [47] Tao Huang and Yixue Li. Current progress, challenges, and future perspectives of language models for protein representation and protein design. The Innovation, 4(4):100446, 2023. ISSN 2666-6758. doi: https://doi.org/10.1016/j.xinn.2023.100446. URL https://www

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