papers

Publications (5)

q-bio.BM2024

Protein Conformation Generation via Force-Guided SE(3) Diffusion Models

Yan Wang, Lihao Wang, Yuning Shen +4

The conformational landscape of proteins is crucial to understanding their functionality in complex biological processes. Traditional physics-based computational methods, such as m…

cs.LG2023

Learning Harmonic Molecular Representations on Riemannian Manifold

Yiqun Wang, Yuning Shen, Shi Chen +3

Molecular representation learning plays a crucial role in AI-assisted drug discovery research. Encoding 3D molecular structures through Euclidean neural networks has become the pre…

cs.LG2025

ConfRover: Simultaneous Modeling of Protein Conformation and Dynamics via Autoregression

Yuning Shen, Lihao Wang, Huizhuo Yuan +3

Understanding protein dynamics is critical for elucidating their biological functions. The increasing availability of molecular dynamics (MD) data enables the training of deep gene…

cs.LG2026

Scalable Spatio-Temporal SE(3) Diffusion for Long-Horizon Protein Dynamics

Nima Shoghi, Yuxuan Liu, Yuning Shen +3

Molecular dynamics (MD) simulations remain the gold standard for studying protein dynamics, but their computational cost limits access to biologically relevant timescales. Recent g…

q-bio.QM2024

ProteinBench: A Holistic Evaluation of Protein Foundation Models

Fei Ye, Zaixiang Zheng, Dongyu Xue +7

Recent years have witnessed a surge in the development of protein foundation models, significantly improving performance in protein prediction and generative tasks ranging from 3D…