IDEAL-Age: an interpretable deep learning framework for single-cell resolution profiling of immunological aging
Yin Xu, Zhengchao Luo, Kai He, Feifan Zhang, Yawei Zhang, Jinzhuo Wang, Han Wen, Yongge Li, Dali Han
IDEAL-Age is a deep learning framework that profiles immunological aging at single-cell resolution, showing improved predictive performance and revealing cellular contributions to aging processes.
Genome biology · Jul 26, 2026Peer-reviewedBioinformatics