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Updated: May 4, 2026

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预测多种细胞类型的多种原始编辑系统的效率

Goosang Yu1, Hui Kwon Kim2, Jinman Park1

  • 1Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Graduate School of Medical Science, Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.

Cell
|April 29, 2023
PubMed
概括

这项研究开发了DeepPrime和DeepPrime-FT计算模型,以预测主要编辑效率. 这些工具通过识别最佳的原始编辑指导RNA (pegRNA) 和原始编辑器 (PE) 来加速原始编辑应用程序.

关键词:
深度学习有效性其他特征高通量评估非目标效应预测情况主要编辑主要编辑一个序列

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