Author

Ming Qin

Army Medical 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

Click to filter author papers

Molecular Biology· 1 Synthetic Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Approach:large language model· 1 Assay:metagenomics· 1

Frequent Co-Authors

Aiping Wang· 1 shared Binbin CheniD· 1 shared Feng Ye· 1 shared Guorong DaniD· 1 shared Haoran YuiD· 1 shared He Tang· 1 shared Hongbing Song· 1 shared Hongying Chen· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperMolecular Biology

Aiping Wang

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Vitamin D3 attenuates nitrogen mustard-induced dermal toxicity by enhancing microbial butyrate production via the intestinal VDR-α-defensin signaling pathway

Xunhu Dong, Ying He, X D Hu, Ze Zhang, Feng Ye, Hongying Chen, Ming Qin, Xiaogang Wang, Yuanpeng Zhao, Guorong Dan, Jiqing Zhao, He Tang, Yan Sai, Aiping Wang, Hongbing Song, , Mingliang Chen

This study shows that Vitamin D3 reduces nitrogen mustard-induced skin damage by boosting gut microbial butyrate production through the VDR-defensin pathway.

bioRxiv · Mar 27, 2026 · PreprintMolecular Biology

Multi-purpose controllable protein generation via prompted language models

Zeyuan Wang, Binbin Chen, Keyan Ding, Jiawen Cao, Ming Qin, Yadan Niu, Xiang Zhuang, Xiaotong Li, Kehua Feng, Tong Xu, Ningyu Zhang, Haoran Yu, Qiang Zhang, Huajun Chen

This paper introduces PROPEND, a protein design method using prompted language models to directly control multiple properties, achieving higher functional recovery than traditional pipelines.

bioRxiv · Nov 17, 2024 · PreprintSynthetic Biology