Author

Yongfei Chang

Zhejiang 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· 1 Genetics· 1 Synthetic Biology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Research Focus:gene regulatory network inference· 2 Assay:CRISPR screen· 1 Research Focus:genome assembly· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:perturbation response prediction· 1 Assay:protein sequence· 1

Frequent Co-Authors

Li XuiD· 2 shared Nga Man Wong· 2 shared Yetong Sang· 2 shared Zehua BaoiD· 2 shared Zhenkun CaiiD· 2 shared Chang-Ting Chen· 1 shared Guimin ZhangiD· 1 shared Jiangning SongiD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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2 shared papersGenetics

Li XuORCID

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Author profile →

3 papers

Recent·Most cited

Repurposing the TIGR-Tas system for programmable transcription activation

Yetong Sang, Li Xu, Nga Man Wong, Yongfei Chang, Zhenkun Cai, Zehua Bao

This paper repurposes the TIGR-Tas system for gene activation, achieving robust and specific transcriptional activation of human genes with a compact system potentially independent of PAMs.

bioRxiv · Aug 5, 2026 · PreprintGenetics

Multiplex genome engineering in yeast using the TIGR-Tas system

Zhenkun Cai, Yetong Sang, Li Xu, Yongfei Chang, Nga Man Wong, Jie Zhu, Chang-Ting Chen, Zehua Bao

This paper demonstrates the use of TIGR-Tas system for multiplex genome engineering in yeast, achieving targeted DNA breaks and gene modifications without PAM requirements.

bioRxiv · Jul 31, 2026 · PreprintSynthetic Biology

HPClas: A data-driven approach for identifying halophilic proteins based on catBoost

Shantong Hu, Xiaoyu Wang, Zhikang Wang, Yongfei Chang, Yun Tian, Zhuoqian Li, Menghan Jiang, Shihui Wang, Wenya Wang, Jiangning Song, Guimin Zhang

HPClas is a machine learning classifier using catBoost to identify halophilic proteins with high accuracy, achieving AUROC scores of 0.877 and 0.845 on training and test sets respectively.

mLife · Jul 20, 2024Peer-reviewedBioinformatics