Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods

C->G transversions can be highly desirable editing outcomes. Here the authors optimise CGBEs and provide a deep learning model for predicting editing outcomes based on sequence context.

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Autores principales:	Tanglong Yuan, Nana Yan, Tianyi Fei, Jitan Zheng, Juan Meng, Nana Li, Jing Liu, Haihang Zhang, Long Xie, Wenqin Ying, Di Li, Lei Shi, Yongsen Sun, Yongyao Li, Yixue Li, Yidi Sun, Erwei Zuo
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/84852509bdb0448faac72ae929a50ecc
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spelling	oai:doaj.org-article:84852509bdb0448faac72ae929a50ecc2021-12-02T16:27:55ZOptimization of C-to-G base editors with sequence context preference predictable by machine learning methods10.1038/s41467-021-25217-y2041-1723https://doaj.org/article/84852509bdb0448faac72ae929a50ecc2021-08-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-25217-yhttps://doaj.org/toc/2041-1723C->G transversions can be highly desirable editing outcomes. Here the authors optimise CGBEs and provide a deep learning model for predicting editing outcomes based on sequence context.Tanglong YuanNana YanTianyi FeiJitan ZhengJuan MengNana LiJing LiuHaihang ZhangLong XieWenqin YingDi LiLei ShiYongsen SunYongyao LiYixue LiYidi SunErwei ZuoNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Tanglong Yuan Nana Yan Tianyi Fei Jitan Zheng Juan Meng Nana Li Jing Liu Haihang Zhang Long Xie Wenqin Ying Di Li Lei Shi Yongsen Sun Yongyao Li Yixue Li Yidi Sun Erwei Zuo Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods
description	C->G transversions can be highly desirable editing outcomes. Here the authors optimise CGBEs and provide a deep learning model for predicting editing outcomes based on sequence context.
format	article
author	Tanglong Yuan Nana Yan Tianyi Fei Jitan Zheng Juan Meng Nana Li Jing Liu Haihang Zhang Long Xie Wenqin Ying Di Li Lei Shi Yongsen Sun Yongyao Li Yixue Li Yidi Sun Erwei Zuo
author_facet	Tanglong Yuan Nana Yan Tianyi Fei Jitan Zheng Juan Meng Nana Li Jing Liu Haihang Zhang Long Xie Wenqin Ying Di Li Lei Shi Yongsen Sun Yongyao Li Yixue Li Yidi Sun Erwei Zuo
author_sort	Tanglong Yuan
title	Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods
title_short	Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods
title_full	Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods
title_fullStr	Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods
title_full_unstemmed	Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods
title_sort	optimization of c-to-g base editors with sequence context preference predictable by machine learning methods
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/84852509bdb0448faac72ae929a50ecc
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Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods

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