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Biorxiv : the Preprint Server for Biology|January 8, 2024
Invariant point message passing for protein side chain packingNicholas Z Randolph, Brian Kuhlman
Proteins|May 25, 2024
Invariant point message passing for protein side chain packingNicholas Z Randolph, Brian Kuhlman
Proceedings of the National Academy of Sciences of the United States of America|January 29, 2024
Transfer learning to leverage larger datasets for improved prediction of protein stability changesHenry Dieckhaus, Michael Brocidiacono, Nicholas Z Randolph, et al.
Proceedings of the National Academy of Sciences of the United States of America|November 30, 2023
In silico evolution of autoinhibitory domains for a PD-L1 antagonist using deep learning modelsOdessa J Goudy, Amrita Nallathambi, Tomoaki Kinjo, et al.
Biorxiv : the Preprint Server for Biology|June 22, 2026
Deep learning based design of buried hydrogen bond networks with HBDesignerHenry Dieckhaus, Brock T Harvey, Tomiris Mulikova, et al.
The Journal of Biological Chemistry|November 9, 2019
Designing protein structures and complexes with the molecular modeling program RosettaBrian Kuhlman
Current Opinion in Structural Biology|April 23, 2004
Exploring folding free energy landscapes using computational protein designBrian Kuhlman, David Baker
Current Protocols|October 13, 2025
Automated Deep Learning-Based Pipelines for Multi-Objective De Novo Protein DesignAmrita Nallathambi, Brian Kuhlman
Protein Science : a Publication of the Protein Society|December 20, 2024
Protein stability models fail to capture epistatic interactions of double point mutationsHenry Dieckhaus, Brian Kuhlman
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