Disentangling Loss Design and Ontology-Aware Architecture in GNN-Based Protein Function Prediction A Controlled Ablation Study
This controlled ablation study reveals that in GNN-based protein function prediction, the proposed Information Accretion-aware loss function is counterproductive, whereas the optimal performance is achieved by combining a GCN architecture with cross-ontology attention and standard binary cross-entropy loss.