Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches

A major challenge in the application of the CRISPR-Cas13d system is to accurately predict its guide-dependent on-target and off-target effect. Here, we perform CRISPR-Cas13d proliferation screens and design a deep learning model, named DeepCas13, to predict the on-target activity from guide sequence...

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Detalles Bibliográficos
Autores principales: Cheng, Xiaolong, Li, Zexu, Shan, Ruocheng, Li, Zihan, Wang, Shengnan, Zhao, Wenchang, Zhang, Han, Chao, Lumen, Peng, Jian, Fei, Teng, Li, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9912244/
https://www.ncbi.nlm.nih.gov/pubmed/36765063
http://dx.doi.org/10.1038/s41467-023-36316-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9912244/
https://www.ncbi.nlm.nih.gov/pubmed/36765063
http://dx.doi.org/10.1038/s41467-023-36316-3

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