AI proteomics perspective

review

AI proteomics perspective: review. 62-author Nature Methods Perspective mapping where AI is reshaping MS-based proteomics: peptide and protein identification and quantification (de novo sequencing among…

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.

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Authors (62)

Yingying Sun, Jun A, Zhiwei Liu, Rui Sun, Liujia Qian, Samuel H. Payne, Wout Bittremieux, Markus Ralser, Chen Li, Yi Chen, Zhen Dong, Yasset Perez-Riverol, Asif Khan, Chris Sander, Ruedi Aebersold, Juan Antonio Vizcaíno, Jonathan R. Krieger, Jianhua Yao, Wen Han, Linfeng Zhang, Yunping Zhu, Yue Xuan, Benjamin Boyang Sun, Liang Qiao, Henning Hermjakob, Haixu Tang, Huanhuan Gao, Yamin Deng, Qing Zhong, Cheng Chang, Nuno Bandeira, Ming Li, Weinan E, Siqi Sun, Yuedong Yang, Gilbert S. Omenn, Yue Zhang, Ping Xu, Yan Fu, Xiaowen Liu, Christopher M. Overall, Yu Wang, Eric W. Deutsch, Luonan Chen, Jürgen Cox, Vadim Demichev, Fuchu He, Jiaxing Huang, Huilin Jin, Chao Liu, Nan Li, Zhongzhi Luan, Jiangning Song, Kaicheng Yu, Wanggen Wan, Tai Wang, Kang Zhang, Le Zhang, Peter A. Bell, Matthias Mann, Bing Zhang, Tiannan Guo

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