Crossmark

Deep learning–driven prediction of on-target activity, off-target risk, and repair outcomes in CRISPR/Cas9: current landscape and multi-scale perspectives

Crossref DOI link: https://doi.org/10.1186/s12967-026-08175-1

Published Online: 2026-04-28

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Du, Weian

Zhang, Tingfeng

Guo, Linyuan

Zheng, Yangyang

Zhang, Haoyang

Zhu, Xiangxing

Tang, Dongsheng

Hu, Hong

Chen, Ling

Liu, Chao
Funding

Funding for this research was provided by:

Guangdong Provincial and National Key Clinical Specialty Construction Project and National Key Clinical Specialty Construction Project, Sanming Project of Medicine in Shenzhen (SZSM202411026)

National Natural Science Foundation of China (82371901)

National Natural Science Foundation of China (82471919)
License Information

Text and Data Mining valid from 2026-04-28

Version of Record valid from 2026-06-15
More Information

Article History

Received: 11 November 2025

Accepted: 15 April 2026

First Online: 28 April 2026

Declarations

:

: Not applicable.

: Not applicable.

: Not applicable.

: Not applicable.

: The authors have declared that no competing interest exists.

Document is current

Any future updates will be listed below