| 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 | 103 | 2021 |
| Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production JC Greenhalgh, SA Fahlberg, BF Pfleger, PA Romero Nature communications 12 (1), 5825, 2021 | 63 | 2021 |
| Machine learning to navigate fitness landscapes for protein engineering CR Freschlin, SA Fahlberg, PA Romero Current opinion in biotechnology 75, 102713, 2022 | 54 | 2022 |
| Neural network extrapolation to distant regions of the protein fitness landscape SA Fahlberg, CR Freschlin, P Heinzelman, PA Romero bioRxiv, 2023 | 2 | 2023 |
| Developing new strategies for protein engineering by extrapolation of machine learning models S Fahlberg, C Freschlin, P Heinzelman, P Romero Journal of Biological Chemistry 299 (3), S115, 2023 | | 2023 |
