Machine Learning Driven Simulations of the SARS-CoV-2 Fitness Landscape from Deep Mutational Scanning Experiments
Aleksander E. P. Durumeric, Sean McCarty, Jay Smith, Jonas Köhler, Katarina Elez, Lluı́s Raich, Patricia Suriana, Terra Sztain
The paper trains machine learning models on deep mutational scanning data to predict SARS-CoV-2 RBD variant fitness and outperforms point mutation averaging in extrapolating to Omicron variants.
Journal of Chemical Information and Modeling · May 6, 2026Peer-reviewedBioinformatics