Machine Learning-Based Retention Time Prediction of Trimethylsilyl Derivatives of Metabolites

Machine Learning-Based Retention Time Prediction of Trimethylsilyl Derivatives of Metabolites

In gas chromatography–mass spectrometry-based untargeted metabolomics, metabolites are identified by comparing mass spectra and chromatographic retention time with reference databases or standard materials. In that sense, machine learning has been used to predict the retention time of metabolites la...

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Bibliographic Details
Main Authors: Sara M. de Cripan, Adrià Cereto-Massagué, Pol Herrero, Andrei Barcaru, Núria Canela, Xavier Domingo-Almenara
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Biomedicines
Subjects:
retention time
retention index
GC-MS
metabolomics
machine-learning
Online Access:https://www.mdpi.com/2227-9059/10/4/879

Internet

https://www.mdpi.com/2227-9059/10/4/879

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