Author

Daqi Wang

Fudan 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 Genetics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Approach:experimental assay· 2 Organism:mouse· 2 Organism:non-human primate· 2 Research Focus:software / tool· 2 Research Focus:benchmarking· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Biyun ZhuiD· 2 shared Chengdong ZhangiD· 2 shared Feng LaniD· 2 shared Honghai Tang· 2 shared Huawei LiiD· 2 shared Jingcheng YangiD· 2 shared Leming M. ShiiD· 2 shared Linghui HouiD· 2 shared

Activity by Year

2021-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersGenetics

Biyun ZhuORCID

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Author profile →

4 papers

Recent·Most cited

Combination of engineered cell type-specific promoters and a high-efficiency AAV capsid restores hearing in adult DFNB1 mice model with demonstrated safety in nonhuman primate

Shao Wei Hu, Cheng Ye, Guannan Geng, Yicheng Zeng, Yihan Bao, Sen Zhang, Chong Cui, Yingting Zhang, Dan Mu, Daqi Wang, Xintai Fan, Ziting Chen, Biyun Zhu, Shuang Han, Hongxing Wang, , Yilai Shu

This paper demonstrates hearing restoration in adult DFNB1 mice using engineered promoters and an AAV capsid, with safety confirmed in nonhuman primates.

bioRxiv · Apr 18, 2026 · PreprintGenetics

Preclinical evaluation of the efficacy and safety of AAV1-hOTOF in mice and non-human primates

Longlong Zhang, Hui Wang, Mengzhao Xun, Honghai Tang, Jinghan Wang, Jun Lv, Biyun Zhu, Yuxin Chen, Daqi Wang, Shaowei Hu, Ziwen Gao, Jianping Liu, Zheng‐Yi Chen, Bing Chen, Huawei Li, Yilai Shu

This study evaluates the efficacy and safety of AAV1-hOTOF gene therapy in mice and non-human primates for treating DFNB9 hearing loss.

Molecular Therapy — Methods & Clinical Development · Nov 10, 2023Peer-reviewedGenetics

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