蛋白质组学
串联质谱法
Boosting(机器学习)
化学
串联质量标签
串联
定量蛋白质组学
质谱法
计算生物学
色谱法
计算机科学
生物
生物化学
材料科学
人工智能
基因
复合材料
作者
Trenton M. Peters-Clarke,Yiran Liang,Keaton L. Mertz,Kenneth W. Lee,Michael S. Westphall,Joshua D. Hinkle,Graeme C. McAlister,John E. P. Syka,Ryan Kelly,Joshua J. Coon
标识
DOI:10.1021/acs.jproteome.4c00076
摘要
Single-cell proteomics is a powerful approach to precisely profile protein landscapes within individual cells toward a comprehensive understanding of proteomic functions and tissue and cellular states. The inherent challenges associated with limited starting material demand heightened analytical sensitivity. Just as advances in sample preparation maximize the amount of material that makes it from the cell to the mass spectrometer, we strive to maximize the number of ions that make it from ion source to the detector. In isobaric tagging experiments, limited reporter ion generation limits quantitative accuracy and precision. The combination of infrared photoactivation and ion parking circumvents the
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