4 citations · 8 across the 12 of their papers we have counts for
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cs.CE2026
GeoCycler: Reward-Aligned 3D Diffusion for Constraint-Conditioned Cyclic Peptide Design
Jingjie Zhang, Hanqun Cao, Haosen Shi +10
Cyclic peptides are attractive therapeutic modalities because their closed-ring topology can improve stability and target specificity. However, de novo cyclic peptide design remain…
cs.CE2024★ 1 cited
D-Flow: Multi-modality Flow Matching for D-peptide Design
Fang Wu, Shuting Jin, Xiangru Tang +3
Among these, D-peptides are resistant to proteolysis, exhibit greater in vivo stability, and are easier to synthesize. Despite advances in deep learning for peptide discovery, the…