Author

Yongli Peng

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· 3

Signature Assays, Organisms & Methods

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Organism:mouse· 3 Research Focus:cell type annotation· 2 Assay:Hi-C· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:chromatin & epigenetic regulation· 1 Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Hao GeiD· 3 shared Jinzhu JiaiD· 2 shared Dong XingiD· 1 shared Feng TianiD· 1 shared Fuchou TangiD· 1 shared Ge GaoiD· 1 shared Liyuan Yang· 1 shared Menghan Liu· 1 shared

Activity by Year

2021-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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3 shared papersBioinformatics

Hao GeORCID

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3 papers

Recent·Most cited

scSTEC: Annotating Chromatin Subcompartments from Individual Single-Cell Hi-C Data via Direct Two-Dimensional Embedding and Chromosome-wise Consensus

Yongli Peng, Liyuan Yang, Hao Ge

scSTEC directly annotates chromatin subcompartments from individual single-cell Hi-C matrices without imputation or cross-cell sharing, achieving results comparable to scGHOST with greater interpretability.

bioRxiv · Nov 3, 2026 · PreprintBioinformatics

scDIAGRAM: Detecting Chromatin Compartments from Individual Single-Cell Hi-C Matrix without Imputation or Reference Features

Yongli Peng, Yujing Deng, Menghan Liu, Zhiyuan Liu, Ya-Hui Li, Xiang-Yu Zhao, Dong Xing, Jinzhu Jia, Hao Ge

scDIAGRAM detects chromatin compartments in single-cell Hi-C data without imputation or reference features, showing accuracy in simulated and real datasets.

Briefings in Bioinformatics · Feb 11, 2026Peer-reviewedBioinformatics

Direct Reconstruction of Gene Regulatory Networks underlying Cellular state Transitions without Pseudo-time Inference

Ruosi Wan, Yuhao Zhang, Yongli Peng, Feng Tian, Ge Gao, Fuchou Tang, Xiaoliang S. Xie, Jinzhu Jia, Hao Ge

This paper introduces COSLIR, a method to directly reconstruct gene regulatory networks from time-stamped single-cell data without pseudo-time inference, showing good performance on real datasets.

bioRxiv · May 12, 2021 · PreprintBioinformatics