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Predicting prime editing efficiency and product purity by deep learning
Prime editing is a versatile genome editing tool but requires experimental optimization of the prime editing guide RNA (pegRNA) to achieve high editing efficiency. Here, we conducted a high-throughput screen to analyze prime editing outcomes of 92,423 pegRNAs on a highly diverse set of 13,349 human...
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| 出版年: | Nat Biotechnol |
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| 主要な著者: | , , , , , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2023
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7614945/ https://ncbi.nlm.nih.gov/pubmed/36646933 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41587-022-01613-7 |
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