most citedDiffusion Language Models Are Versatile Protein Learners

18 citations · 29 across the 6 of their papers we have counts for

collaborators

6 papers

q-bio.BM2025★ 1 cited

SeedProteo: Accurate De Novo All-Atom Design of Protein Binders

Wei Qu, Yiming Ma, Fei Ye +6

We present SeedProteo, a diffusion-based model for de novo all-atom protein design. We demonstrate how to repurpose a cutting-edge folding architecture into a powerful generative d…

cs.LG2025

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.…

q-bio.BM2024

ProteinWeaver: A Divide-and-Assembly Approach for Protein Backbone Design

Yiming Ma, Fei Ye, Yi Zhou +3

Nature creates diverse proteins through a 'divide and assembly' strategy. Inspired by this idea, we introduce ProteinWeaver, a two-stage framework for protein backbone design. Our…

cs.LG2024★ 7 cited

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…

q-bio.QM2024★ 3 cited

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…

cs.LG2024★ 18 cited

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…