Author

Nicholas Z. Randolph

University of North Carolina at Chapel HillORCID 0000-0003-1092-324XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioengineering· 1 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein design· 2 Assay:protein sequence· 1 Assay:protein structure· 1

Frequent Co-Authors

Brian A. KuhlmaniD· 2 shared Henry DieckhausiD· 2 shared Brock T. HarveyiD· 1 shared Jessica T Horenstein· 1 shared Michael BrocidiaconoiD· 1 shared Nathan I. NicelyiD· 1 shared Tomiris MulikovaiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 17 mutual co-author links

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2 shared papersBioengineering

Brian A. KuhlmanORCID

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2 papers

Recent·Most cited

BioengineeringbioRxivPreprintSep 30, 2026

Deep learning based design of buried hydrogen bond networks with HBDesigner

Henry Dieckhaus, Brock T. Harvey, Tomiris Mulikova…·Brian A. Kuhlman

This paper introduces HBDesigner, a deep learning tool for designing hydrogen-bond networks in proteins, showing improved performance over existing methods.

DOI 10.64898/2026.06.08.730848

protein structuredeep learning

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BioinformaticsProceedings of the National Academy of SciencesPeer-reviewedJan 29, 2024

Transfer learning to leverage larger datasets for improved prediction of protein stability changes

Henry Dieckhaus, Michael Brocidiacono, Nicholas Z. Randolph, Brian A. Kuhlman

This paper introduces ThermoMPNN, a deep learning model for predicting protein stability changes using transfer learning and a large dataset, achieving competitive performance on benchmarks.

205 citationstop 1%

protein sequencedeep learning

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