Identification of biological signatures of cruciferous vegetable consumption utilizing machine learning-based global untargeted stable isotope traced metabolomics

In recent years there has been increased interest in identifying biological signatures of food consumption for use as biomarkers. Traditional metabolomics-based biomarker discovery approaches rely on multivariate statistics which cannot differentiate between host- and food-derived compounds, thus no...

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Hlavní autoři:	John A. Bouranis, Yijie Ren, Laura M. Beaver, Jaewoo Choi, Carmen P. Wong, Lily He, Maret G. Traber, Jennifer Kelly, Sarah L. Booth, Jan F. Stevens, Xiaoli Z. Fern, Emily Ho
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Frontiers Media S.A. 2024-07-01
Edice:	Frontiers in Nutrition
Témata:	cruciferous vegetables metabolomics stable isotope tracing machine learning precision nutrition
On-line přístup:	https://www.frontiersin.org/articles/10.3389/fnut.2024.1390223/full
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