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Ai Translational Medicine

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Ai Translational Medicine

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Research Frontiers in Graph Neural Networks for Drug Discovery

Leverages graph-based deep learning to model molecular interactions and predict drug efficacy and toxicity profiles.

Molecular Graph Topology and Binding Affinity Prediction
Equivariant Neural Networks for 3D Protein-Ligand Interactions
Graph Heterogeneity in Multi-Modal Biomedical Knowledge Integration
Message Passing Dynamics in Drug Resistance Networks
Interpretable Graph Attention for Target Identification
Generalization Across Chemical Space in GNN Models
Temporal Graph Networks in Drug Repurposing
Graph Neural Networks for Polypharmacology and Off-Target Effects
Scalable GNN Architectures for Protein Interaction Networks
Uncertainty Quantification in Graph-Based Molecular Screening

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