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SpCas9 activity prediction by DeepSpCas9, a deep learning-based model with high generalization performance

Authors
 Hui Kwon Kim  ;  Younggwang Kim  ;  Sungtae Lee  ;  Seonwoo Min  ;  Jung Yoon Bae  ;  Jae Woo Choi  ;  Jinman Park  ;  Dongmin Jung  ;  Sungroh Yoon  ;  Hyongbum Henry Kim 
Citation
 Science Advances, Vol.5(11) : eaax9249, 2019 
Journal Title
 Science Advances 
Issue Date
2019
Abstract
We evaluated SpCas9 activities at 12,832 target sequences using a high-throughput approach based on a human cell library containing single-guide RNA-encoding and target sequence pairs. Deep learning-based training on this large dataset of SpCas9-induced indel frequencies led to the development of a SpCas9 activity-predicting model named DeepSpCas9. When tested against independently generated datasets (our own and those published by other groups), DeepSpCas9 showed high generalization performance. DeepSpCas9 is available at http://deepcrispr.info/DeepSpCas9.
Files in This Item:
T201904612.pdf Download
DOI
10.1126/sciadv.aax9249
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Pharmacology (약리학교실) > 1. Journal Papers
Yonsei Authors
Kim, Hyongbum(김형범) ORCID logo https://orcid.org/0000-0002-4693-738X
Bae, Jung Yoon(배정윤) ORCID logo https://orcid.org/0000-0001-8342-6987
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/173417
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