A generalizable Cas9/sgRNA prediction model using machine transfer learning with small high-quality datasets.

Ham, Dalton T; Browne, Tyler S; Banglorewala, Pooja N; Wilson, Tyler L; Michael, Richard K; Gloor, Gregory B; Edgell, David R

Ham, Dalton T; Browne, Tyler S; Banglorewala, Pooja N; Wilson, Tyler L; Michael, Richard K; Gloor, Gregory B; Edgell, David R.

Afiliação

Ham DT; Department of Biochemistry, Schulich School of Medicine and Dentistry, London, ON, N6A5C1, Canada.
Browne TS; Department of Biochemistry, Schulich School of Medicine and Dentistry, London, ON, N6A5C1, Canada.
Banglorewala PN; Department of Biochemistry, Schulich School of Medicine and Dentistry, London, ON, N6A5C1, Canada.
Wilson TL; Tesseraqt Optimization Inc, Toronto, ON, Canada.
Michael RK; Tesseraqt Optimization Inc, Toronto, ON, Canada.
Gloor GB; Department of Biochemistry, Schulich School of Medicine and Dentistry, London, ON, N6A5C1, Canada. ggloor@uwo.ca.
Edgell DR; Department of Biochemistry, Schulich School of Medicine and Dentistry, London, ON, N6A5C1, Canada. dedgell@uwo.ca.

Nat Commun ; 14(1): 5514, 2023 09 07.

Article em En | MEDLINE | ID: mdl-37679324

Assuntos

Sistemas CRISPR-Cas; RNA Guia de Sistemas CRISPR-Cas; Sistemas CRISPR-Cas/genética; Confiabilidade dos Dados; Endonucleases; Aprendizado de Máquina

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Sistemas CRISPR-Cas / RNA Guia de Sistemas CRISPR-Cas Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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