Author

Wen-Jie Jiang

Peking University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2 Microbiology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:deep learning· 2 Assay:Hi-C· 2 Assay:scRNA-seq· 2 Approach:statistical model· 2 Research Focus:cell-cell communication· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Hua‐Jun WuiD· 3 shared Nana WeiiD· 3 shared An Liu· 2 shared Futing Lai· 2 shared Hanwen ZhuiD· 2 shared Kangwen Cai· 2 shared Xiaoqi ZhengiD· 2 shared Yuanchen Sun· 2 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 40 mutual co-author links

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3 shared papersBioinformatics

Hua‐Jun WuORCID

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3 papers

Recent·Most cited

BioinformaticsGenome biologyPeer-reviewedJan 21, 2026

Harmonizing single cell 3D genome data with STARK and scNucleome

Wen-Jie Jiang, Kangwen Cai, Sun Yuanchen…·Hua‐Jun Wu

The paper introduces STARK, a toolkit for processing sc3DG-seq data, benchmarks 11 technologies, and establishes scNucleome as a resource for 3D genome research.

1 citation

scRNA-seqHi-C

𝕏 PostBluesky

MicrobiologybioRxivPreprintDec 4, 2025

Exploring multi-level microbial interactions from individual 3D genomes to community networks

Wen-Jie Jiang, Kang-Wen Cai, Yuanchen Sun…·Hua‐Jun Wu

This study introduces FindMeta3D to analyze microbial 3D genomes and cross-domain interactions, revealing conserved chromatin patterns and infection-related hotspots with therapeutic implications.

DOI 10.64898/2025.12.03.692222

Hi-Cdeep learning

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BioinformaticsbioRxivPreprintNov 15, 2024

CellPatch: a Highly Efficient Foundation Model for Single-Cell Transcriptomics with Heuristic Patching

Hanwen Zhu, Yushun Yuan, Jiyuan Yang…·Hua‐Jun Wu

CellPatch is a lightweight foundation model for single-cell transcriptomics that achieves state-of-the-art performance with low computational costs.

DOI 10.1101/2024.11.15.623701

humanscRNA-seq

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