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Deep learning models to predict the editing efficiencies and outcomes of diverse base editors

Nahye Kim, Sung-Chul Choi, Sungjae Kim, Myungjae Song, Jung Hwa Seo, Seonwoo Min, Jinman Park, Sung‐Rae Cho, Seokjoong Kim

2023Nature Biotechnology69 citationsDOIOpen Access PDF

Topics & Concepts

Cas9CRISPRComputational biologyBase (topology)Genome editingCytosineComputer scienceDeep learningGuide RNABiologyArtificial intelligenceGeneticsDNAGeneMathematicsMathematical analysisCRISPR and Genetic EngineeringRNA regulation and diseaseRNA and protein synthesis mechanisms
Deep learning models to predict the editing efficiencies and outcomes of diverse base editors | Litcius