AI-driven CRISPR screening: optimizing gene editing through automation and intelligent decision support
Together, ML/DL and LLM-agent approaches reframe CRISPR screening from a static analytical pipeline into an intelligent experimental system, with important implications for robustness, scalability and biological discovery.
Authors
- Yuxi Zhao
- Xingrui Li (ORCID: https://orcid.org/0000-0001-9312-9935)
- Yaying Du
Institutions
- Tongji Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- Journal of Translational Medicine
- Published
- 2026-02-19
- DOI
- https://doi.org/10.1186/s12967-026-07849-0
- Primary Topic
- CRISPR and Genetic Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00