Data availability
The proteomics data, the spectral library, and sample information generated in this study have been deposited in PRIDE under the accession number PXD059608. The remaining data are available within the Article, Supplementary Data files or Source Data file. Source data are providd with this paper. Source data are provided with this paper.
Code availability
The computational framework ProteoAutoNet, including R and Python scripts and visualized files, is publicly available at: https://github.com/guomics-lab/ProteoAutoNet. The code and example files that were used in this study are publicly available on Zenodo at https://doi.org/10.5281/zenodo.18217457.
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Acknowledgements
This work is supported by grants from Joint Funds of the National Natural Science Foundation of China (No. U24A20476) to T.G., National Key R&D Program of China (No. 2021YFA1301600) to T.G., National Natural Science Foundation of China (Young Scientist Fund, No. 32401239) to R.S., Zhejiang Provincial Natural Science Foundation of China (LQ24C050002) to R.S., the State Key Laboratory of Medical Proteomics (SKLP-Y202403) to R.S. and Key Technology Research and Development Program of Shandong Province (2022CXGC020510) to X.L. We thank Westlake University Supercomputer Center for assistance in data generation and storage, and the Mass Spectrometry & Metabolomics Core Facility at the Center for Biomedical Research Core Facilities of Westlake University for sample analysis. We thank Prof. Ruedi Aebersold, Dr. Moritz Heusel and Dr. Chen Li for helpful discussions, and Prof. Leonard Foster and Jenny Moon for advice on sample preparation. We also thank Liang Chen for helping with figures.
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Competing interests
T. G. is a shareholder of Westlake Omics Inc. P.L. is a staff of Westlake Omics Inc. The remaining authors declare no competing interests.
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Lyu, M., Hu, P., Zhang, G. et al. ProteoAutoNet: high-throughput co-eluted protein analysis with robotics and machine learning. Nat Commun (2026). https://doi.org/10.1038/s41467-026-68686-9
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DOI: https://doi.org/10.1038/s41467-026-68686-9
