Author

Chenchen Han

Chinese Academy of SciencesORCID 0000-0002-3330-5308Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:protein sequence· 2 Approach:deep learning· 1 Approach:large language model· 1 Approach:machine learning (classical)· 1 Research Focus:protein design· 1 Research Focus:sequence-to-function modeling· 1 Research Focus:software / tool· 1

Frequent Co-Authors

An‐Ping ZengiD· 2 shared Fajie YuaniD· 2 shared Fengyuan Dai· 2 shared Jin SuiD· 2 shared Tong SiiD· 2 shared Xing ChangiD· 2 shared Yan HeiD· 2 shared Yuliang Fan· 2 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioengineering

An‐Ping ZengORCID

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2 papers

Recent·Most cited

Toward De Novo Protein Design from Natural Language

Fengyuan Dai, Shiyang You, Yudian Zhu, Yuan Gao, Lihao Fu, Xibin Zhou, Jin Su, Chentong Wang, Yuliang Fan, Qingsong Tan, Xiaoxiao Ma, Xianjun Deng, Letong Yu, Hui Qian, Yan He, , Fajie Yuan

This paper introduces Pinal, a foundation model that designs proteins from natural language descriptions, achieving functional alignment and experimental success in four design tasks.

Nature · Oct 21, 2026Peer-reviewedBioengineering

Democratizing Protein Language Model Training, Sharing and Collaboration

Jin Su, Zhikai Li, Tianli Tao, Chenchen Han, Yan He, Fengyuan Dai, Qingyan Yuan, Yuan Gao, Tong Si, Xuting Zhang, Yuyang Zhou, Junjie Shan, Xibin Zhou, Xing Chang, Shiyu Jiang, , Sergey Ovchinnikov

The paper introduces SaprotHub, a platform that simplifies training and sharing of protein language models, enabling non-experts to build and collaborate on customized models.

Nature Biotechnology · Oct 24, 2025Peer-reviewedBioinformatics