crossrefMachine Learning2026-07-21
Learning from Dynamic Protein Interaction Networks with State-Memory Temporal Graph Neural Networks
Manuel Dileo, Andrea Sottoriva
Abstract Modeling the temporal evolution of biological systems is fundamental for understanding cellular dynamics and anticipating future functional states. While temporal graph neural networks (TGNNs) have achieved remarkable success in social and financial domains, their evalua…