Author

Piyu Zhou

Chinese Academy of Sciences

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· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Assay:proteomics· 1 Research Focus:software / tool· 1 Approach:statistical model· 1 Assay:whole-genome sequencing· 1 Organism:yeast· 1

Frequent Co-Authors

Di ZhangiD· 1 shared Guoqing Hu· 1 shared Haipeng WangiD· 1 shared Hao ChiiD· 1 shared Jiaxin Dai· 1 shared Jinghan YangiD· 1 shared Jingyan Li· 1 shared Kang LiiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperBioinformatics

Di ZhangORCID

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2 papers

Recent·Most cited

Primitive GLMY Homology: An Algebraic Topology Approach for the Quantitative Characterization of Graph Pangenomes toward Population Genetic Analysis

Qi Wu, Jingyan Li, Guoqing Hu, Piyu Zhou, Xin Zhao, Stephen S.‐T. Yau

This paper introduces Primitive GLMY Homology to quantitatively analyze graph pangenomes and applies it to population genetic analysis in yeast.

bioRxiv · Jul 16, 2026 · PreprintGenetics

DiNovo: high-coverage, high-confidence de novo peptide sequencing using mirror proteases and deep learning

Zixuan Cao, Xueli Peng, Di Zhang, Piyu Zhou, Kang Li, Hao Chi, Ruitao Wu, Zhiyuan Cheng, Yao Zhang, Jiaxin Dai, Yanchang Li, Lijin Yao, Xinming Li, Jinghan Yang, Haipeng Wang, , Yan Fu

DiNovo improves de novo peptide sequencing by using mirror proteases and deep learning, achieving higher coverage and confidence than single-protease methods.

bioRxiv · Mar 20, 2025 · PreprintBioinformatics