Deep learning–driven prediction of on-target activity, off-target risk, and repair outcomes in CRISPR/Cas9: current landscape and multi-scale perspectives

Abstract The CRISPR/Cas9 system has emerged as a transformative tool in genome editing, playing a pivotal role in enabling precise genetic engineering. Achieving high on-target efficiency while minimizing off-target activity is critical for translating CRISPR/Cas9 into reliable experimental and ther...

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主要な著者:	Weian Du, Tingfeng Zhang, Linyuan Guo, Yangyang Zheng, Haoyang Zhang, Xiangxing Zhu, Dongsheng Tang, Hong Hu, Ling Chen, Chao Liu
フォーマット:	Artigo
言語:	Inglês
出版事項:	BMC 2026-04-01
シリーズ:	Journal of Translational Medicine
主題:	CRISPR/Cas9 Genome editing Deep learning sgRNA design
オンライン･アクセス:	https://doi.org/10.1186/s12967-026-08175-1
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