Predicting CRISPR/Cas9-Induced Mutations for Precise Genome Editing

被引：43

作者：

Molla, Kutubuddin A. ^{[1
,2
,3
]}

Yang, Yinong ^{[1
,2
]}

机构：

[1] Penn State Univ, Dept Plant Pathol & Environm Microbiol, University Pk, PA 16802 USA

[2] Penn State Univ, Huck Inst Life Sci, University Pk, PA 16802 USA

[3] Natl Rice Res Inst, ICAR, Cuttack 753006, Orissa, India

来源：

TRENDS IN BIOTECHNOLOGY | 2020年 / 38卷 / 02期

基金：

美国国家科学基金会; 美国食品与农业研究所;

关键词：

Genes - Machine learning;

D O I：

10.1016/j.tibtech.2019.08.002

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

SpCas9 creates blunt end cuts in the genome and generates random and unpredictable mutations through error-prone repair systems. However, a growing body of recent evidence points instead to Cas9-induced staggered end generation, nonrandomness of mutations, and the predictability of editing outcomes using machine learning models.

引用

收藏

页码：136 / 141

页数：7

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