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Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches
Xiaolong Cheng, Zexu Li, Ruocheng Shan, Zihan Li, Lumen Chao, Jian Peng, Teng Fei, View ORCID ProfileWei Li
doi: https://doi.org/10.1101/2021.09.02.458773
Xiaolong Cheng
1Center for Genetic Medicine Research, Children’s National Hospital. Washington, DC, USA 20010
2Department of Genomics and Precision Medicine, George Washington University, Washington, DC, USA 20010
Zexu Li
3College of Life and Health Sciences, Northeastern University, Shenyang, China
Ruocheng Shan
1Center for Genetic Medicine Research, Children’s National Hospital. Washington, DC, USA 20010
4Department of Computer Science, George Washington University, Washington, DC, USA
Zihan Li
3College of Life and Health Sciences, Northeastern University, Shenyang, China
Lumen Chao
1Center for Genetic Medicine Research, Children’s National Hospital. Washington, DC, USA 20010
2Department of Genomics and Precision Medicine, George Washington University, Washington, DC, USA 20010
Jian Peng
5Department of Computer Science, University of Illinois at Urbana-Champaign. Urbana, IL 61801
Teng Fei
3College of Life and Health Sciences, Northeastern University, Shenyang, China
Wei Li
1Center for Genetic Medicine Research, Children’s National Hospital. Washington, DC, USA 20010
2Department of Genomics and Precision Medicine, George Washington University, Washington, DC, USA 20010
Posted September 04, 2021.
Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches
Xiaolong Cheng, Zexu Li, Ruocheng Shan, Zihan Li, Lumen Chao, Jian Peng, Teng Fei, Wei Li
bioRxiv 2021.09.02.458773; doi: https://doi.org/10.1101/2021.09.02.458773
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