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Ai Biomarkers

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Ai Biomarkers

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Research Frontiers in Graph Neural Networks Protein Interactions

Using graph-based deep learning to model and predict protein-protein interactions as disease biomarkers.

Topological Signatures in Dynamic Protein Interaction Networks
Graph Attention Mechanisms for Cryptic Binding Site Discovery
Heterogeneous Network Embeddings in Multi-Omics Biomarker Detection
Temporal Graph Neural Networks in Protein Conformational Transitions
Message Passing Architectures for Allosteric Communication Prediction
Graph Pooling Strategies in Subnetwork Biomarker Extraction
Equivariant Graph Networks for 3D Protein Complex Assembly
Interpretable Graph Convolutions in Disease-Associated Interaction Rewiring
Spectral Methods for Hidden Modularity in Signaling Cascade Networks
Graph Generative Models in Synthetic Biomarker Construction

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