Author

Xiang Zhang

University of British ColumbiaORCID 0000-0002-4146-3584Unclaimed ORCID profile · follow to get notified of new preprints

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Xiang Zhang4 papers · Baylor College of Medicine

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:deconvolution· 2 Approach:deep learning· 2 Assay:proteomics· 2 Approach:transformer / foundation model· 2 Research Focus:benchmarking· 1 Organism:human· 1 Organism:mouse· 1 Organism:plant (other)· 1

Frequent Co-Authors

Nanqing DongiD· 2 shared A Jun· 1 shared Boyan SuniD· 1 shared Cheng ChangiD· 1 shared Guangshuai Wang· 1 shared Guibin WangiD· 1 shared Jiaqi WeiiD· 1 shared Laks V. S. LakshmananiD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

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10 top collaborators · 31 mutual co-author links

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2 shared papersBioinformatics

Nanqing DongORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJun 20, 2025

MassNet: billion-scale AI-friendly mass spectral corpus enables robust de novo peptide sequencing

A Jun, Xiang Zhang, Xiaofan Zhang…·Tiannan Guo

MassNet provides a large-scale mass spectral corpus for proteomics, enabling AI-driven de novo peptide sequencing with improved performance over existing methods.

2 citations

𝕏 PostBluesky

BioinformaticsbioRxivPreprintMay 17, 2024

π-PrimeNovo: An Accurate and Efficient Non-Autoregressive Deep Learning Model for De Novo Peptide Sequencing

Xiang Zhang, Tianze Ling, Zhi Xiang Jin…·Siqi Sun

π-PrimeNovo is a non-autoregressive deep learning model for de novo peptide sequencing that achieves higher accuracy and 69x faster performance than existing methods.

1 citation

proteomicsdeep learning

𝕏 PostBluesky