Author

Ling Lin

Fudan UniversityORCID 0000-0002-6766-5432Unclaimed ORCID profile · follow to get notified of new preprints

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Ling Lin2 papers · Aarhus University

Biology Disciplines

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Systems Biology· 2 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:proteomics· 3 Research Focus:differential expression· 2 Assay:metabolomics· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:clustering· 1

Frequent Co-Authors

Liang QiaoiD· 2 shared Andreas SchereriD· 1 shared Bao Fu DingiD· 1 shared Baozhen ShaniD· 1 shared Bin LiiD· 1 shared Bingying LiiD· 1 shared Chen DingiD· 1 shared Dan ZhaoiD· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersCancer Biology

Liang QiaoORCID

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3 papers

Recent·Most cited

Cancer BiologyAnalytical ChemistryPeer-reviewedDec 30, 2024

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

Yi Yang, Dan Zhao, Ji Luo…·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.

5 citations

humanproteomics

𝕏 PostBluesky

Systems BiologybioRxivPreprintMar 30, 2023

Single-cell time-resolved multi-omics reveal apoptotic and ferroptotic heterogeneity during foam cell formation

Yiwen Wang, Ling Lin, Liang Qiao

The paper uses single-cell time-resolved multi-omics to reveal apoptotic and ferroptotic heterogeneity in macrophage-derived foam cells during atherosclerosis progression.

DOI 10.1101/2023.03.30.534700

𝕏 PostBluesky

Systems BiologybioRxivPreprintOct 24, 2022

Ratio-based quantitative multiomics profiling using universal reference materials empowers data integration

Yuanting Zheng, Yaqing Liu, Jingcheng Yang…·Leming M. Shi

This paper introduces ratio-based multiomics profiling using universal reference materials to improve data integration across omics types and batches.

DOI 10.1101/2022.10.24.513612

humanDNA methylation

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