Author

Xiehua Ouyang

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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Biochemistry· 1 Bioinformatics· 1 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:proteomics· 3 Approach:experimental assay· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Hao WuiD· 3 shared Yi WangiD· 2 shared Yonghao ZhangiD· 2 shared Ban ZhaoiD· 1 shared Jiakai Fang· 1 shared Libing WangiD· 1 shared Xuechun Gao· 1 shared Yonghui MaoiD· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 21 mutual co-author links

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3 shared papersMolecular Biology

Hao WuORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Automated SP3 Workflow Enables Robust Sample Preparation on Proteonano Ultraplex Proteomics Platform

Yi Wang, Libing Wang, Yonghao Zhang, Xiehua Ouyang, Hao Wu

The paper evaluates three proteomics sample preparation methods, finding that automated SP3 (autoSP3) provides high consistency and scalability for proteomics workflows.

bioRxiv · May 27, 2025 · PreprintMolecular Biology

Proteonano: A Robust Platform for Large Cohort Deep Plasma Proteomic Studies

Hao Wu, Yonghao Zhang, Yi Wang, Xiehua Ouyang

The paper introduces a platform for large-scale plasma proteomics studies that improves the detection of low-abundant proteins and enables biomarker discovery in neurodegenerative diseases.

bioRxiv · Aug 20, 2024 · PreprintBiochemistry

Proteonano: a novel deep proteomics platform with 1000-plex profiling capacity and picogram sensitivity and its application in diabetic kidney disease

Ban Zhao, Xuechun Gao, Xiehua Ouyang, Jiakai Fang, Zihao Deng, Hao Wu, Yonghui Mao

The paper introduces a deep proteomics platform called Proteonano with high sensitivity and wide dynamic range, identifying novel biomarkers for diabetic kidney disease progression.

bioRxiv · Sep 12, 2023 · PreprintBioinformatics