Simplifying protein engineering with deep learning.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 40845808.
- Also identified by DOI 10.1016/j.cell.2025.07.037.
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Abstract
When it comes to deep learning for protein engineering, there is strength in simplicity. In this issue of Cell, through thoughtful deployment of existing fixed-backbone sequence design models, Caixia Gao and colleagues engineer diverse genome editing systems with improved functionality, enabling powerful capabilities in fine-grained and large-scale genome editing as demonstrated through strong experimental validation.
Medical subject headings
- Deep Learning
- Protein Engineering