Author

B. Koepnick

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Biophysics· 2 Scientific Communication & Education· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein design· 2 Assay:protein sequence· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:software / tool· 1

Frequent Co-Authors

D. Baker· 3 shared B. I. M. Wicky· 2 shared I. Anishchenko· 2 shared N. P. King· 2 shared A. Bera· 1 shared A. Courbet· 1 shared A. Feichtenbiner· 1 shared A. Kang· 1 shared

Activity by Year

2020-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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3 shared papersBiophysics

D. Baker

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Author profile →

3 papers

Recent·Most cited

Robust deep learning based protein sequence design using ProteinMPNN

J. Dauparas, I. Anishchenko, N. Bennett, H. Bai, R. J. Ragotte, L. F. Milles, B. I. M. Wicky, A. Courbet, R. J. de Haas, N. Bethel, P. J. Y. Leung, T. F. Huddy, S. Pellock, D. Tischer, F. Chan, , D. Baker

A deep learning method for protein sequence design shows high performance in both simulations and experiments, applicable to various design challenges.

bioRxiv · Jun 3, 2022Biophysics

Increasing computational protein design literacy through cohort-based learning for undergraduate students

E. C. Yang, R. Divine, C. S. Kang, S. Chan, E. Arenas, Z. Subol, P. Tinker, H. Manninen, A. Feichtenbiner, T. Mustafa, J. Hallowell, I. Orr, H. Haddox, B. Koepnick, J. O'Connor, , N. P. King

This paper describes a remote cohort-based curriculum for undergraduate students to learn computational protein design, enhancing their research skills and connecting them with the lab.

bioRxiv · May 24, 2022Scientific Communication & Education

Protein sequence design by explicit energy landscape optimization

C. Norn, B. I. M. Wicky, D. Juergens, S. Liu, D. Kim, B. Koepnick, I. Anishchenko, Foldit Players, D. Baker, S. Ovchinnikov

This paper designs protein sequences by optimizing an energy landscape to ensure they fold into a desired structure, showing improved performance over traditional methods.

bioRxiv · Jul 23, 2020 · PreprintBiophysics