Author

Yi Yang

Fudan UniversityORCID 0000-0002-1330-9985Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Yi Yang9 papers · Johns Hopkins University

Biology Disciplines

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Bioinformatics· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Assay:proteomics· 3 Research Focus:benchmarking· 2 Organism:human· 2 Approach:statistical model· 2 Organism:bacteria (other)· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Liang QiaoiD· 3 shared Baozhen ShaniD· 1 shared Chengpin SheniD· 1 shared Dan ZhaoiD· 1 shared Enhui Wu· 1 shared Guoquan Yan· 1 shared Hebin LiuiD· 1 shared Hongxu Chen· 1 shared

Activity by Year

2021-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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3 shared papersBioinformatics

Liang QiaoORCID

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3 papers

Recent·Most cited

Quantitative site-specific glycoproteomics by ZenoTOF reveals glyco-signatures for breast cancer diagnosis

Yi Yang, Dan Zhao, Ji Luo, Ling Lin, Yuxiang Lin, Baozhen Shan, Hongxu Chen, Liang Qiao

The paper uses ZenoTOF mass spectrometry to analyze glycoproteomes from breast cancer and control samples, identifying 15 site-specific glycans as potential biomarkers for breast cancer detection.

Analytical Chemistry · Dec 30, 2024Peer-reviewedCancer Biology

Contigs directed gene annotation (ConDiGA) for accurate protein sequence database construction in metaproteomics

Enhui Wu, Vijini Mallawaarachchi, Jinzhi Zhao, Yi Yang, Hebin Liu, Xiaoqing Wang, Chengpin Shen, Yu Lin, Liang Qiao

The paper introduces ConDiGA, a pipeline for constructing accurate protein sequence databases from metagenomic data to improve metaproteomics analysis, achieving deep coverage in synthetic and real microbiota samples.

Microbiome · Mar 19, 2024Peer-reviewedBioinformatics

GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control

Yi Yang, Guoquan Yan, Siyuan Kong, Mengxi Wu, Pengyuan Yang, Weiqian Cao, Liang Qiao

GproDIA improves glycoproteomics by enabling accurate glycopeptide identification and quantification using DIA data with comprehensive statistical control.

Nature Communications · Oct 18, 2021Peer-reviewedBioinformatics