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Sam Gelman
Sam Gelman
Machine Learning Scientist, Morgridge Institute for Research
Verified email at wisc.edu
Title
Cited by
Cited by
Year
Neural networks to learn protein sequence–function relationships from deep mutational scanning data
S Gelman, SA Fahlberg, P Heinzelman, PA Romero, A Gitter
Proceedings of the National Academy of Sciences 118 (48), e2104878118, 2021
1032021
Biophysics-based protein language models for protein engineering
S Gelman, B Johnson, C Freschlin, S D'Costa, A Gitter, PA Romero
bioRxiv, 2024.03. 15.585128, 2024
2024
Green fluorescent protein engineering with a biophysics-based protein language model
S Gelman, B Johnson, CR Freschlin, S D'Costa, A Gitter, P Romero
ICLR 2024 Workshop on Generative and Experimental Perspectives for …, 0
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