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Updated: Jun 30, 2026

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
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在没有长期质量控制的情况下提高代谢学数据的可比性,使用获得后校正策略

Elfried Salanon1, Blandine Comte1, Delphine Centeno1

  • 1Université Clermont Auvergne, INRAE, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, Clermont-Ferrand, France.

Analytica chimica acta
|November 15, 2025
PubMed
概括

一项名为PARSEC的新策略通过标准化和过原始数据来提高代谢学数据的可比性. 这种方法增强了研究间的比较,并揭示了以前被分析变异性隐藏的生物学见解.

关键词:
批量效应是一个效应.集团效应的影响代谢学 代谢学 代谢学收购后的标准化标准化

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