GAE-Δ: A Graph-Learning Framework for Gene Network Rewiring and Clinical Outcome Prediction from Multi-Omics Data
Zhiyong Tang, Zhe Chen, Mengting Chen, Yihua Wang, Sarah Ennis, Mahesan Niranjan, Rob M. Ewing
GAE-Δ uses a graph autoencoder to analyze multi-omics data and predict clinical outcomes while identifying gene network rewiring associated with cancer progression.
bioRxiv · May 26, 2026 · PreprintBioinformatics