A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action
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DOI: 10.1371/journal.pcbi.1005807
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- Qinchang Chen & Guohui Chuai & Haihang Zhang & Jin Tang & Liwen Duan & Huan Guan & Wenhui Li & Wannian Li & Jiaying Wen & Erwei Zuo & Qing Zhang & Qi Liu, 2023. "Genome-wide CRISPR off-target prediction and optimization using RNA-DNA interaction fingerprints," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
- Xiaoguang Pan & Kunli Qu & Hao Yuan & Xi Xiang & Christian Anthon & Liubov Pashkova & Xue Liang & Peng Han & Giulia I. Corsi & Fengping Xu & Ping Liu & Jiayan Zhong & Yan Zhou & Tao Ma & Hui Jiang & J, 2022. "Massively targeted evaluation of therapeutic CRISPR off-targets in cells," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
- Hsiu-Hui Tsai & Hsiao-Jung Kao & Ming-Wei Kuo & Chin-Hsien Lin & Chun-Min Chang & Yi-Yin Chen & Hsiao-Huei Chen & Pui-Yan Kwok & Alice L. Yu & John Yu, 2023. "Whole genomic analysis reveals atypical non-homologous off-target large structural variants induced by CRISPR-Cas9-mediated genome editing," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
- Sebastian M. Siegner & Laura Ugalde & Alexandra Clemens & Laura Garcia-Garcia & Juan A. Bueren & Paula Rio & Mehmet E. Karasu & Jacob E. Corn, 2022. "Adenine base editing efficiently restores the function of Fanconi anemia hematopoietic stem and progenitor cells," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
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