清脆的
生物信息学
引导RNA
计算生物学
生物
亚基因组mRNA
Cas9
鉴定(生物学)
基因组编辑
核糖核酸
计算机科学
人工智能
遗传学
基因
植物
作者
Guohui Chuai,Hanhui Ma,Jifang Yan,Ming Chen,Nanfang Hong,Dongyu Xue,Chi Zhou,Chenyu Zhu,Ke Chen,Bin Duan,Feng Gu,Sheng Qu,De-Shuang Huang,Jia Wei,Qi Liu
出处
期刊:Genome Biology
[BioMed Central]
日期:2018-06-26
卷期号:19 (1)
被引量:414
标识
DOI:10.1186/s13059-018-1459-4
摘要
A major challenge for effective application of CRISPR systems is to accurately predict the single guide RNA (sgRNA) on-target knockout efficacy and off-target profile, which would facilitate the optimized design of sgRNAs with high sensitivity and specificity. Here we present DeepCRISPR, a comprehensive computational platform to unify sgRNA on-target and off-target site prediction into one framework with deep learning, surpassing available state-of-the-art in silico tools. In addition, DeepCRISPR fully automates the identification of sequence and epigenetic features that may affect sgRNA knockout efficacy in a data-driven manner. DeepCRISPR is available at http://www.deepcrispr.net/ .
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