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Updated: Jun 12, 2026

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
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对COVID-19代谢学的元分析确定了生物标志物的稳定性变化

Anthony Onoja1, Johanna von Gerichten2, Holly-May Lewis3

  • 1School of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK.

International journal of molecular sciences
|September 28, 2023
PubMed
概括

这项研究使用代谢学验证了COVID-19生物标志物,发现一个由9个生物标志物组成的小组显示了最强大的表现. 这些发现强调了对未来传染病进行可再生生物标志物研究的需要.

关键词:
在 COVID-19 疫情中,生物标志物 生物标志物诊断 诊断 诊断 诊断 诊断未来的流行病 未来的流行病机器学习是机器学习.质谱测量质谱测量质谱测量质谱测量质量测量质谱测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量代谢生物组的代谢生物组验证验证的时间

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