4 citations · 4 across the 5 of their papers we have counts for
5 papers
SE(3)-MeanFlow: Few-Step Protein Backbone Generation on Lie Groups
Yikun Bai, Binghang Lu, Yikai Liu +7
Generative modeling of protein backbones promises the de novo design of proteins with prescribed structural and functional properties. Existing diffusion and flow-matching models p…
Fine-Tuning Diffusion Models for Molecular Generation via Reinforcement Learning and Fast Sampling
Guang Lin, Shikui Tu, Lei Xu
Generating molecules that simultaneously satisfy drug-like properties and conform to the 3D structure of a target protein is a core challenge in structure-based drug design (SBDD).…
ProTDyn: a foundation Protein language model for Thermodynamics and Dynamics generation
Yikai Liu, Haoyang Zheng, Lining Mao +3
Molecular dynamics (MD) simulation has long been the principal computational tool for exploring protein conformational landscapes and dynamics, but its application is limited by hi…
Unbiasing Enhanced Sampling on a High-dimensional Free Energy Surface with Deep Generative Model
Yikai Liu, Tushar K. Ghosh, Guang Lin +1
Biased enhanced sampling methods utilizing collective variables (CVs) are powerful tools for sampling conformational ensembles. Due to high intrinsic dimensions, efficiently genera…
Backdiff: a diffusion model for generalized transferable protein backmapping
Yikai Liu, Ming Chen, Guang Lin
Coarse-grained (CG) models play a crucial role in the study of protein structures, protein thermodynamic properties, and protein conformation dynamics. Due to the information loss…