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UniGenX: a unified generative foundation model that couples sequence, structure and function to accelerate scientific design across proteins, molecules and materials

Fuente: arXiv

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Bibliographic Details
Main Authors:	Zhang, Gongbo, Li, Yanting, Luo, Renqian, Hu, Pipi, Yang, Yang, Zhao, Zeru, Li, Lingbo, Liu, Guoqing, Wang, Zun, Bi, Ran, Gao, Kaiyuan, Guo, Liya, Xie, Yu, Liu, Chang, Zhang, Jia, Xie, Tian, Pinsler, Robert, Zeni, Claudio, Lu, Ziheng, Hao, Hongxia, Xia, Yingce, Segler, Marwin, Riechert, Maik, Yang, Wei, Jiang, Hao, Zhang, Wen-Bin, Zeng, Zhijun, Zhu, Yi, Dong, Li, Hu, Xiuyuan, Yuan, Li, Chen, Lei, Liu, Haiguang, Qin, Tao
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Materials Science Artificial Intelligence Biological Physics Chemical Physics
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2503.06687