GT-Mamba: A Topology-Aware Graph-State Space Model for Robust and Interpretable Epigenetic Age Prediction (opens in new tab)

AbstractMotivationCurrent epigenetic clocks face a trade-off between predictive accuracy and biological interpretability, often relying on dataset-specific correction to generalize across cohorts. We propose GT-Mamba, a novel architecture that integrates a Structure-Aware Graph Transformer with the Mamba state space model. This design captures CpG topological correlations and genome-wide long-range dependencies.ResultsGT-Mamba demonstrates strong out-of-the-box robustness across heterogeneous...