Author

Yonghong He

Tsinghua Shenzhen International Graduate SchoolORCID 0000-0002-9964-8901Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Assay:proteomics· 2 Research Focus:deconvolution· 1 Research Focus:protein folding & dynamics· 1 Assay:protein sequence· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

Frequent Co-Authors

Cheng ChangiD· 2 shared Fuchu HeiD· 2 shared Linhai XieiD· 2 shared Tianze LingiD· 2 shared Tingpeng YangiD· 2 shared Zhendong LiangiD· 2 shared Athanasios V. Vasilakos· 1 shared Boyan SuniD· 1 shared

Activity by Year

2023-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 34 mutual co-author links

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2 shared papersBioinformatics

Cheng ChangORCID

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3 papers

Recent·Most cited

False discovery rate control enables trustworthy deep-learning-based de novo peptide sequencing

Zhendong Liang, Chengxin Dai, Tianze Ling, Tingpeng Yang, Yun Yang, Yeye Leng, Linhai Xie, Yonghong He, Fuchu He, Yue Wang, Cheng Chang

This paper introduces a method to control false discovery rates in deep-learning-based de novo peptide sequencing, improving reliability of peptide identifications.

bioRxiv · Jun 29, 2026 · PreprintBioinformatics

Improving Variant Effect Prediction by Steering Sparse Mechanistic Features in Protein Language Models

Mingqing Wang, Meng Yuan, Athanasios V. Vasilakos, Yonghong He, Zhixiang Ren

This paper improves variant effect prediction by modifying protein language models with sparse mechanistic features, achieving significant performance gains across multiple datasets.

bioRxiv · May 15, 2026 · PreprintBioinformatics

Introducing π-HelixNovo for practical large-scale de novo peptide sequencing

Tingpeng Yang, Tianze Ling, Boyan Sun, Zhendong Liang, Fan Xu, Xiansong Huang, Linhai Xie, Yonghong He, Leyuan Li, Fuchu He, Yu Wang, Cheng Chang

The paper introduces π-HelixNovo, a Transformer-based model for de novo peptide sequencing that outperforms existing methods and improves taxonomic resolution in gut metaproteomes.

bioRxiv · Jul 15, 2023 · PreprintBioinformatics