18 citations · 44 across the 12 of their papers we have counts for
12 papers
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…
Protein Autoregressive Modeling via Multiscale Structure Generation
Yanru Qu, Cheng-Yen Hsieh, Zaixiang Zheng +2
We present protein autoregressive modeling (PAR), the first multi-scale autoregressive framework for protein backbone generation via coarse-to-fine next-scale prediction. Using the…
Designing Cyclic Peptides via Harmonic SDE with Atom-Bond Modeling
Xiangxin Zhou, Mingyu Li, Yi Xiao +5
Cyclic peptides offer inherent advantages in pharmaceuticals. For example, cyclic peptides are more resistant to enzymatic hydrolysis compared to linear peptides and usually exhibi…
An All-Atom Generative Model for Designing Protein Complexes
Ruizhe Chen, Dongyu Xue, Xiangxin Zhou +3
Proteins typically exist in complexes, interacting with other proteins or biomolecules to perform their specific biological roles. Research on single-chain protein modeling has bee…
Elucidating the Design Space of Multimodal Protein Language Models
Cheng-Yen Hsieh, Xinyou Wang, Daiheng Zhang +5
Multimodal protein language models (PLMs) integrate sequence and token-based structural information, serving as a powerful foundation for protein modeling, generation, and design.…
DPLM-2: A Multimodal Diffusion Protein Language Model
Xinyou Wang, Zaixiang Zheng, Fei Ye +3
Proteins are essential macromolecules defined by their amino acid sequences, which determine their three-dimensional structures and, consequently, their functions in all living org…
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…
Decomposed Direct Preference Optimization for Structure-Based Drug Design
Xiwei Cheng, Xiangxin Zhou, Yuwei Yang +2
Diffusion models have achieved promising results for Structure-Based Drug Design (SBDD). Nevertheless, high-quality protein subpocket and ligand data are relatively scarce, which h…
DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization
Xiangxin Zhou, Xiwei Cheng, Yuwei Yang +3
Recently, 3D generative models have shown promising performances in structure-based drug design by learning to generate ligands given target binding sites. However, only modeling t…
Antigen-Specific Antibody Design via Direct Energy-based Preference Optimization
Xiangxin Zhou, Dongyu Xue, Ruizhe Chen +3
Antibody design, a crucial task with significant implications across various disciplines such as therapeutics and biology, presents considerable challenges due to its intricate nat…
Diffusion Language Models Are Versatile Protein Learners
Xinyou Wang, Zaixiang Zheng, Fei Ye +3
This paper introduces diffusion protein language model (DPLM), a versatile protein language model that demonstrates strong generative and predictive capabilities for protein sequen…
Pure Exploration in Asynchronous Federated Bandits
Zichen Wang, Chuanhao Li, Chenyu Song +3
We study the federated pure exploration problem of multi-armed bandits and linear bandits, where agents cooperatively identify the best arm via communicating with the central s…