Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens

Base editors are chimeric ribonucleoprotein complexes consisting of a DNA-targeting CRISPR-Cas module and a single-stranded DNA deaminase. They enable transition of C•G into T•A base pairs and vice versa on genomic DNA. While base editors have great potential as genome editing tools for basic resear...

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Detalles Bibliográficos
Autores principales: Marquart, Kim F., Allam, Ahmed, Janjuha, Sharan, Sintsova, Anna, Villiger, Lukas, Frey, Nina, Krauthammer, Michael, Schwank, Gerald
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8387386/
https://www.ncbi.nlm.nih.gov/pubmed/34433819
http://dx.doi.org/10.1038/s41467-021-25375-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8387386/
https://www.ncbi.nlm.nih.gov/pubmed/34433819
http://dx.doi.org/10.1038/s41467-021-25375-z

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