A predictive framework for stop-loss variants with C-terminal extensions
Jihoon G. Yoon, S. Lee, Yoonjung Kim, Heon Yung Gee, Min Goo Lee, Kyung-A Lee
The paper develops TAILVAR, a machine-learning classifier to predict the functional impact of stop-loss variants by integrating multi-omics features, and shows it outperforms existing tools.
Nucleic Acids Research · Jan 14, 2026Peer-reviewedGenetics