Predicting prime editing efficiency and product purity by deep learningNicolas Mathis, Gerald Schwank, Ahmed Allam et al.|Nature Biotechnology|2023Cited by 145
Machine learning prediction of prime editing efficiency across diverse chromatin contextsNicolas Mathis, Gerald Schwank, Lucas Kissling et al.|Nature Biotechnology|2024Cited by 57
Effective genome editing with an enhanced ISDra2 TnpB system and deep learning-predicted ωRNAsKim Fabiano Marquart, Gerald Schwank, Nicolas Mathis et al.|Nature Methods|2024Cited by 29
Predicting prime editing efficiency across diverse edit types and chromatin contexts with machine learningNicolas Mathis, Gerald Schwank, Ahmed Allam et al.|bioRxiv (Cold Spring Harbor Laboratory)|2023Cited by 8
Publisher Correction: Machine learning prediction of prime editing efficiency across diverse chromatin contextsNicolas Mathis, Gerald Schwank, Ahmed Allam et al.|Nature Biotechnology|2024Cited by 4