Author

Yuening Zhang

Shanghai Jiao Tong 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 Physiology· 1

Signature Assays, Organisms & Methods

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Research Focus:software / tool· 3 Approach:deep learning· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1

Frequent Co-Authors

Chengdong ZhangiD· 2 shared Daqi Wang· 2 shared Feng LaniD· 2 shared Jingcheng YangiD· 2 shared Leming M. ShiiD· 2 shared Linghui HouiD· 2 shared Sang‐Ging OngiD· 2 shared Tao Qi· 2 shared

Activity by Year

2021-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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2 shared papersBioinformatics

Chengdong ZhangORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Biological Aging of the Cardiopulmonary System

D K Liu, Pramath Doddaballapur, Zhongyu Cai, Rira Choi, Jack Di Palo, Nicole M. Guerrera, Nebal Abu Hussein, Meredith S. Gwin, Liqin Lin, Siming Zheng, Yuening Zhang, A. Justet, Abhay B. Ramachandra, Xiting Yan, Edward P. Manning

This study quantifies biological cardiopulmonary aging in mice by integrating biomechanics and single-cell transcriptomics, revealing non-linear aging patterns and cell-type-specific gene expression changes.

bioRxiv · Jun 12, 2026 · PreprintPhysiology

BMAP: a comprehensive and reproducible biomedical data analysis platform

Yongyong Ren, Zhiwei Cheng, Leijie Li, Yuening Zhang, Fang Dai, Luojia Deng, Yijie Wu, Jianlei Gu, Qingmin Lin, Xiaolei Wang, Yan Kong, Hui Dong Lu

BMAP provides a platform for managing and analyzing biomedical data, improving reproducibility and efficiency in research workflows.

bioRxiv · Jul 15, 2024 · PreprintBioinformatics

BEdeepon: an in silico tool for prediction of base editor efficiencies and outcomes

Chengdong Zhang, Zimeng Yu, Daqi Wang, Tao Qi, Yuening Zhang, Linghui Hou, Feng Lan, Jingcheng Yang, Leming M. Shi, Sang‐Ging Ong, Hongyan Wang, Yongming Wang

BEdeepon predicts base editor efficiencies and outcome sequences using deep learning models trained on high-throughput screening data.

bioRxiv · Mar 14, 2021 · PreprintBioinformatics

BEdeepoff: an in silico tool for off-target prediction of ABE and CBE base editors

Chengdong Zhang, Daqi Wang, Tao Qi, Yuening Zhang, Linghui Hou, Feng Lan, Jingcheng Yang, Sang‐Ging Ong, Hongyan Wang, Leming M. Shi, Yongming Wang

BEdeepoff predicts off-target editing efficiencies for ABE and CBE base editors using deep learning models trained on high-throughput screening data.

bioRxiv · Mar 14, 2021 · PreprintBioinformatics