12 citations · 17 across the 5 of their papers we have counts for
5 papers
AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model
Changze Lv, Jiang Zhou, Siyu Long +22
We introduce AMix-1, a powerful protein foundation model built on Bayesian Flow Networks and empowered by a systematic training methodology, encompassing pretraining scaling laws,…
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…
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…
Autaptic Synaptic Circuit Enhances Spatio-temporal Predictive Learning of Spiking Neural Networks
Lihao Wang, Zhaofei Yu
Spiking Neural Networks (SNNs) emulate the integrated-fire-leak mechanism found in biological neurons, offering a compelling combination of biological realism and energy efficiency…
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…