Author

Shuaiyi Liang

ORCID 0009-0007-6343-9933Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Assay:multiome· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Gang WangiD· 2 shared Hubin CheniD· 2 shared Jiemei ChuiD· 2 shared Jingyi LiiD· 2 shared Sanqi AniD· 2 shared Yao LiniD· 2 shared Yue-Qi LiiD· 2 shared Hao LiangiD· 1 shared

Activity by Year

2024-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 43 mutual co-author links

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2 shared papersBioinformatics

Gang WangORCID

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2 papers

Recent·Most cited

BioinformaticsGenomics Proteomics & BioinformaticsPeer-reviewedJul 5, 2024

Pan-cancer Analysis Reveals m6A Variation and Cell-specific Regulatory Network in Different Cancer Types

Yao Lin, Jingyi Li, Shuaiyi Liang…·Sanqi An

The paper analyzes m6A methylomes across nine human tissues to show how m6A variation contributes to tumor heterogeneity and clinical outcomes in different cancer types.

31 citationstop 4%

humanmultiome

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BioinformaticsGenomics Proteomics & BioinformaticsPeer-reviewedJun 7, 2024

Scm6A: A fast and low-cost method for quantifying m6A modifications at the single-cell level

Yue-Qi Li, Jingyi Li, Wenxing Li…·Sanqi An

Scm6A is a machine learning method for single-cell m6A quantification, validated against m6A-seq and showing strong correlation in T-cells and disease samples.

13 citations

humanmachine learning (classical)

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