Wayment-Steele HK#, Otten R#, Pitsawong W#, Ojoawo A#, Glaser A, Calderone LA & Kern D. The conformational landscape of fold-switcher KaiB is tuned to the circadian rhythm timescale. PNAS 2024
Zhang Z#, Wayment-Steele HK#, Brixi G, Wang H, Kern D & Ovchinnikov S. Protein language models learn evolutionary statistics of interacting sequence motifs. PNAS 2024
Wayment-Steele HK#, Ojoawo A#, Otten R, Apitz JM, Pitsawong W, Hoemberger M, Ovchinnikov S, Colwell L & Kern D. Predicting multiple conformations via sequence clustering and AlphaFold2. Nature 2023
Wayment-Steele, HK#, Kladwang, W#, Watkins, AM#, Kim, DS#, Tunguz, B#, … Das, R. Deep learning models for predicting RNA degradation via dual crowdsourcing. Nature Machine Intelligence 2022
Wayment-Steele, HK, Kladwang, W, Strom, A. I., Becka, A., Lee, J., Treuille, A., Eterna Participants, Das, R. RNA secondary structure packages evaluated and improved by high-throughput experiments. Nature Methods 2022
Leppek, K.#, Byeon, GW#, Kladwang, W#, Wayment-Steele, HK#, Kerr, CH#, … Barna, M, Das, R. Combinatorial optimization of mRNA structure, stability, and translation for RNA-based therapeutics. Nature Communications 2022
Andreasson, JO, Gotrik, MR, Wu, MJ, Wayment-Steele, HK, Kladwang, W, Portela, F, Wellington-Oguri, R., Eterna Participants, Das, R., Greenleaf, W. J. Crowdsourced RNA design discovers diverse, reversible, efficient, self-contained molecular sensors. PNAS 2022
Wayment-Steele, HK, Kim, DS, Choe, CA, Nicol, JJ, Wellington-Oguri, R, Sperberg, RAP, Huang, P, Eterna Participants, Das, R. Theoretical basis for stabilizing messenger RNA through secondary structure design. Nucleic Acids Research 2021
Kostrz, D, Wayment-Steele, HK, Wang, J. L., Follenfant, M., Pande, V. S., Strick, T. R., Gosse, C. A modular DNA scaffold to study protein–protein interactions at single-molecule resolution. Nature Nanotechnology 2019
Wayment-Steele, HK, Pande, VS Variational encoding of protein dynamics benefits from maximizing latent autocorrelation. The Journal of Chemical Physics 2018
Hernandez, CX#, Wayment-Steele, HK#, Sultan, MM#, Husic, BE, Pande, VS. Variational Encoding of Complex Dynamics. Physical Review E 2018
Sultan, MM, Wayment-Steele, HK, Pande, VS. Transferable neural networks for enhanced sampling of protein dynamics. Journal of Chemical Theory and Computation 2018
Husic, BE, McKiernan, KA, Wayment-Steele, HK, Sultan, MM, Pande, VS. A minimum variance clustering approach produces robust and interpretable coarse-grained models. Journal of Chemical Theory and Computation 2018