Author

Qing Sheng Xie

The Ohio State UniversityORCID 0000-0003-1926-1457Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Assay:Hi-C· 2 Research Focus:imputation· 2 Approach:Bayesian inference· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:statistical model· 1

Frequent Co-Authors

Shili LiniD· 2 shared Chenggong Han· 1 shared Victor X. JiniD· 1 shared Wang Meng· 1 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 4 mutual co-author links

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2 shared papersBioinformatics

Shili LinORCID

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2 papers

Recent·Most cited

BioinformaticsBMC BioinformaticsPeer-reviewedMay 21, 2025

scHiCSRS: A Self-Representation Smoothing Method with Gaussian Mixture Model for Imputing single-cell Hi-C Data

Qing Sheng Xie, Wang Meng, Shili Lin

scHiCSRS improves scHi-C data quality by distinguishing structural zeros from dropouts, leading to more accurate clustering in downstream analysis.

1 citation

Hi-Cstatistical model

𝕏 PostBluesky

GeneticsPLoS Computational BiologyPeer-reviewedJun 13, 2022

HiCImpute: A Bayesian Hierarchical Model for Identifying Structural Zeros and Enhancing Single Cell Hi-C Data.

Qing Sheng Xie, Chenggong Han, Victor X. Jin, Shili Lin

HiCImpute identifies structural zeros in scHi-C data and improves imputation, leading to more accurate clustering and subtype discovery in neuronal cells.

12 citations

Hi-CBayesian inference

𝕏 PostBluesky