AI proteomics: from protein identification to virtual cells

peer-reviewed · Nature Methods · 2026

peer-reviewed · Nature Methods · 2026. Yingying Sun et al.
Date 2026-07-28
Type peer-reviewed
Venue Nature Methods
Publisher Springer Nature
Contribution review
DOI 10.1038/s41592-026-03085-y
Citations (OpenAlex) 1
Venue 2-year citedness 20.00

Authors

  1. Yingying Sun · Westlake University
  2. Jun A · Westlake University
  3. Zhiwei Liu · Westlake University
  4. Rui Sun · Westlake University
  5. Liujia Qian · Westlake University
  6. Samuel H. Payne · Brigham Young University
  7. Wout Bittremieux · Indiana University, University of Antwerp, University of California San Diego
  8. Markus Ralser · Charité – Universitätsmedizin Berlin
  9. Chen Li · Monash University
  10. Yi Chen · Westlake University
  11. Zhen Dong · Westlake University
  12. Yasset Perez-Riverol · European Molecular Biology Laboratory
  13. Asif Khan · Harvard Medical School
  14. Chris Sander · Harvard Medical School
  15. Ruedi Aebersold · ETH Zurich
  16. Juan Antonio Vizcaíno · European Molecular Biology Laboratory
  17. Jonathan R. Krieger · Bruker Ltd.
  18. Jianhua Yao · Tencent
  19. Wen Han · AI for Science Institute
  20. Linfeng Zhang · AI for Science Institute
  21. Yunping Zhu · Beijing Institute of Lifeomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing)
  22. Yue Xuan · Thermo Fisher Scientific GmbH
  23. Benjamin Boyang Sun · Bristol Myers Squibb
  24. Liang Qiao · Fudan University
  25. Henning Hermjakob · European Molecular Biology Laboratory
  26. Haixu Tang · Indiana University, Indiana University Bloomington, University of California San Diego
  27. Huanhuan Gao · Westlake University
  28. Yamin Deng · Westlake University
  29. Qing Zhong · The University of Sydney
  30. Cheng Chang · Beijing Institute of Lifeomics, International Academy of Phronesis Medicine (Guangdong), National Center for Protein Sciences (Beijing), State Key Laboratory of Medical Proteomics
  31. Nuno Bandeira · University of California San Diego
  32. Ming Li · Bioinformatics Solutions Inc., Peng Cheng Laboratory, University of Waterloo, University of Western Ontario
  33. Weinan E · AI for Science Institute, Peking University
  34. Siqi Sun · Fudan University, Shanghai Artificial Intelligence Laboratory
  35. Yuedong Yang · Sun Yat-sen University
  36. Gilbert S. Omenn · University of Michigan
  37. Yue Zhang · Westlake University
  38. Ping Xu · Beijing Institute of Lifeomics, China Medical University, National Center for Protein Sciences (Beijing)
  39. Yan Fu · Chinese Academy of Sciences, University of Chinese Academy of Sciences
  40. Xiaowen Liu · Tulane University
  41. Christopher M. Overall · University of British Columbia
  42. Yu Wang · Peng Cheng Laboratory
  43. Eric W. Deutsch · Institute for Systems Biology
  44. Luonan Chen · Shanghai Jiao Tong University
  45. Jürgen Cox · Max Planck Institute of Biochemistry, University of Bergen
  46. Vadim Demichev · Charité – Universitätsmedizin Berlin
  47. Fuchu He · Beijing Institute of Lifeomics, International Academy of Phronesis Medicine (Guangdong), National Center for Protein Sciences (Beijing), State Key Laboratory of Medical Proteomics
  48. Jiaxing Huang · Westlake University
  49. Huilin Jin · Anhui University
  50. Chao Liu · Beihang University, Chinese Academy of Sciences, University of Chinese Academy of Sciences
  51. Nan Li · Westlake University
  52. Zhongzhi Luan · Beihang University
  53. Jiangning Song · Monash University
  54. Kaicheng Yu · Westlake University
  55. Wanggen Wan · Shanghai University
  56. Tai Wang · Bristol Myers Squibb
  57. Kang Zhang · Wenzhou Medical University
  58. Le Zhang · Sichuan University
  59. Peter A. Bell · University of British Columbia
  60. Matthias Mann · European Molecular Biology Laboratory, Max Planck Institute of Biochemistry
  61. Bing Zhang · Baylor College of Medicine
  62. Tiannan Guo · Westlake Institute for Advanced Study, Westlake University

Methods and tools

  • AI proteomics perspective: 62-author Nature Methods Perspective mapping where AI is reshaping MS-based proteomics: peptide and protein identification and quantification (de novo sequencing among them), protein-protein interactions and complexes, spatial and perturbation proteomics, multi-omics integration, and ultimately AI virtual cells. Closes with a call for an AI-friendly data ecosystem for the field.

Cites (3)

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