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Motif Prediction

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Motif Prediction

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Research Frontiers in Graph Neural Networks for 3D Protein Motif Recognition

Leveraging graph-based deep learning to identify three-dimensional structural motifs in protein folding and protein-protein interaction networks.

Equivariant Graph Learning for Conformational Motif Discovery
Hierarchical Attention Mechanisms in Protein Fold Recognition
Geometric Deep Learning at the Amino Acid Interface
Message Passing Networks for Allosteric Motif Detection
Sparse 3D Convolutions in Cryptic Binding Site Prediction
Graph Pooling Strategies for Multiscale Protein Architecture
Rotational Invariance and Motif Generalization Across Species
Neural Implicit Representations of Protein Surface Topology
Temporal Graph Networks for Dynamic Motif Transitions
Self-Supervised Contrastive Learning in Structure Space

All Motif Prediction PhD categories