Author

Junping Li

Xidian UniversityORCID 0000-0001-7377-5518Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Research Focus:dimensionality reduction· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:experimental assay· 1 Assay:Hi-C· 1 Approach:matrix factorization· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Lin GaoiD· 2 shared Han XuiD· 1 shared Jiadong LiniD· 1 shared Runzhi Xie· 1 shared Senpeng Zhang· 1 shared Weibing WangiD· 1 shared Yangzhan Ye· 1 shared Yusen YeiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 24 mutual co-author links

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2 shared papersBioinformatics

Lin GaoORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintSep 8, 2026

Atlas-scale single-cell analysis beyond in-memory paradigm with scAtlasPy

Han Xu, Yangzhan Ye, Senpeng Zhang…·Lin Gao

scAtlasPy enables efficient analysis of large single-cell atlases by using disk-resident computing, achieving high speed and low memory usage compared to existing tools.

DOI 10.64898/2026.09.03.748766

scRNA-seqexperimental assay

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BioinformaticsBMC GenomicsPeer-reviewedMay 6, 2026

BandHiC: a memory-efficient and user-friendly Python package for organizing and analyzing Hi-C matrices down to sub-kilobase resolution

Weibing Wang, Junping Li, Yusen Ye, Lin Gao

BandHiC reduces memory usage for Hi-C matrices by 99% using a banded storage strategy while enabling efficient analysis of ultra-high-resolution data.

DOI 10.1186/s12864-026-12680-4

Hi-Cstatistical model

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