Author

Xinzhou Qian

Fudan University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:protein design· 2 Approach:graph neural network· 1 Assay:protein sequence· 1 Assay:proteomics· 1

Frequent Co-Authors

Gaoxing Guo· 2 shared Qiang HuangiD· 2 shared Xiaoming HeiD· 2 shared Jiaqiang QianiD· 1 shared Lei Wang· 1 shared Lei WangiD· 1 shared Liangwei Guo· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 18 mutual co-author links

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2 shared papersBioinformatics

Gaoxing Guo

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2 papers

Recent·Most cited

Computational nanobody design using graph neural networks and Metropolis Monte Carlo sampling

Lei Wang, Xiaoming He, Xinzhou Qian, Gaoxing Guo, Qiang Huang

This paper develops a computational method using graph neural networks and Metropolis Monte Carlo sampling to design high-affinity nanobodies, achieving a Pearson correlation of 0.62 on benchmark.

Briefings in Bioinformatics · Mar 1, 2026Peer-reviewedBioinformatics

De novo design of protein-binding aptamers through deep reinforcement learning assembly of nucleic acid fragments

Gaoxing Guo, Liangwei Guo, Jiaqiang Qian, Xiaoming He, Xinzhou Qian, Lei Wang, Qiang Huang

This paper introduces AiDTA, a deep reinforcement learning method for de novo design of protein-binding aptamers, achieving high-affinity DNA aptamers for disease-related proteins.

bioRxiv · Jun 1, 2025 · PreprintBioinformatics