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AI proteomics: from protein identification to virtual cells
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PRE
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李
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陈
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张
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DOI：10.1038/s41592-026-03085-y.png)
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Abstract
En 中文
Artificial intelligence (AI) is transforming scientific research, including proteomics. In this Perspective, we highlight key mass spectrometry (MS)-based proteomics areas where AI is driving innovation, ranging from protein identification to building AI virtual cells. These include improving peptide and protein identification and quantification; characterizing protein-protein interactions and protein complexes; advancing spatial and perturbation proteomics; integrating multi-omics data; and, ultimately, enabling AI virtual cells. Finally, we call for global collaboration among data producers, data consumers and other stakeholders to establish an AI-friendly ecosystem for MS-based proteomics, laying the foundation for transformative advancements in proteomics driven by AI. This Perspective highlights key research areas within mass spectrometry-based proteomics where AI is poised to drive significant advances.
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