Publication: Machine learning prediction of prime editing efficiency across diverse chromatin contexts
Machine learning prediction of prime editing efficiency across diverse chromatin contexts
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Mathis, N., Allam, A., Tálas, A., Kissling, L., Benvenuto, E., Schmidheini, L., Schep, R., Damodharan, T., Balazs, Z., Janjuha, S., Ioannidi, E. I., Böck, D., van Steensel, B., Krauthammer, M., & Schwank, G. (2025). Machine learning prediction of prime editing efficiency across diverse chromatin contexts. Nature Biotechnology, 43(5), 712–719. https://doi.org/10.1038/s41587-024-02268-2
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Creators (Authors)
- Mathis, Nicolas
- Allam, Ahmed
- Tálas, András
- Kissling, Lucas
- Benvenuto, Elena
- Schmidheini, Lukas
- Schep, Ruben
- Damodharan, Tanav
- Balazs, Zsolt
- Janjuha, Sharan
- Ioannidi, Eleonora I
- Böck, Desirée
- van Steensel, Bas
- Krauthammer, Michael
- Schwank, Gerald
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Mathis, N., Allam, A., Tálas, A., Kissling, L., Benvenuto, E., Schmidheini, L., Schep, R., Damodharan, T., Balazs, Z., Janjuha, S., Ioannidi, E. I., Böck, D., van Steensel, B., Krauthammer, M., & Schwank, G. (2025). Machine learning prediction of prime editing efficiency across diverse chromatin contexts. Nature Biotechnology, 43(5), 712–719. https://doi.org/10.1038/s41587-024-02268-2
