Author

Yeye Leng

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

Signature Assays, Organisms & Methods

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Research Focus:protein folding & dynamics· 2 Assay:proteomics· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Organism:human· 1 Organism:mouse· 1

Frequent Co-Authors

Yun YangiD· 2 shared Changying FuiD· 1 shared Cheng ChangiD· 1 shared Chengxin DaiiD· 1 shared Chuanxi Huang· 1 shared Chuping Wei· 1 shared Fuchu HeiD· 1 shared Fuchu HeiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioinformatics

Yun YangORCID

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2 papers

Recent·Most cited

False discovery rate control enables trustworthy deep-learning-based de novo peptide sequencing

Zhendong Liang, Chengxin Dai, Tianze Ling, Tingpeng Yang, Yun Yang, Yeye Leng, Linhai Xie, Yonghong He, Fuchu He, Yue Wang, Cheng Chang

This paper introduces a method to control false discovery rates in deep-learning-based de novo peptide sequencing, improving reliability of peptide identifications.

bioRxiv · Jun 29, 2026 · PreprintBioinformatics

Simple, Fast and Highly Efficient One-or Two-step Proteomic Preparation Enables Deep Profiling of Microgram-level FF and FFPE Tissues

Chuping Wei, Qiuxia Zhang, Changying Fu, Yeye Leng, Chuanxi Huang, Fuchu He, Yun Yang

The paper introduces SWIFT, a fast and efficient proteomic workflow for processing microgram-level FF and FFPE tissues, achieving high repeatability and deep proteome coverage.

Analytical Chemistry · Apr 28, 2026Peer-reviewedBiochemistry