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Ai Structural Biology

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Research Frontiers in Transformer Models for Structure Alignment

Attention-based transformer architectures applied to align and compare complex protein structural features across multiple sequences.

Equivariant Attention in Multi-Chain Protein Alignment
Latent Space Geometry of Structural Homologs
Transformer Cross-Attention for Disordered Region Prediction
Self-Supervised Alignment Beyond Sequence Homology
Attention Mechanisms in Conformational State Transitions
Fine-Grained Motif Discovery Through Transformer Interpretability
Domain Shuffling and Recombination in Deep Structure Networks
Hierarchical Alignment of Evolutionarily Distant Folds
Transformer Memory in Temporal Protein Structure Dynamics
Geometric Constraints in Attention-Based Superposition Learning

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