AI与蛋白质组学融合，推动生物发现新范式
Strategic priorities for transformative progress in advancing biology with proteomics and artificial intelligence
- 构建AI友好的蛋白质组数据生态，实现数据生成与共享
- 提升肽段与蛋白鉴定及定量精度，增强分析可靠性
- 适合生物信息学、系统生物学研究者关注前沿整合技术
人工智能（AI）正在重塑科学研究，包括蛋白质组学。基于质谱（MS）的蛋白质组学数据在质量、多样性与规模上的进步，结合突破性的AI技术，正开启生物发现的新挑战与机遇。本文强调了AI驱动创新的关键领域：构建面向AI的蛋白质组学数据生成、共享与分析生态系统；提升肽段与蛋白的鉴定与定量能力；解析蛋白-蛋白相互作用与蛋白复合物；推进空间与扰动蛋白质组学；实现多组学数据整合；最终目标是构建由AI赋能的虚拟细胞。
原文摘要 · Abstract (English)
Artificial intelligence (AI) is transforming scientific research, including proteomics. Advances in mass spectrometry (MS)-based proteomics data quality, diversity, and scale, combined with groundbreaking AI techniques, are unlocking new challenges and opportunities in biological discovery. Here, we highlight key areas where AI is driving innovation, from data analysis to new biological insights. These include developing an AI-friendly ecosystem for proteomics data generation, sharing, and analysis; 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-empowered virtual cells.
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