MS2Lipid: A Lipid Subclass Prediction Program Using Machine Learning and Curated Tandem Mass Spectral Data

MS2Lipid: A Lipid Subclass Prediction Program Using Machine Learning and Curated Tandem Mass Spectral Data

<b>Background</b>: Untargeted lipidomics using collision-induced dissociation-based tandem mass spectrometry (CID-MS/MS) is essential for biological and clinical applications. However, annotation confidence still relies on manual curation by analytical chemists, despite the development o...

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Bibliographic Details
Main Authors: Nami Sakamoto, Takaki Oka, Yuki Matsuzawa, Kozo Nishida, Jayashankar Jayaprakash, Aya Hori, Makoto Arita, Hiroshi Tsugawa
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Metabolites
Subjects:
untargeted lipidomics
tandem mass spectrum
machine learning
lipid class prediction
microbiota-dependent lipids
human fecal samples
Online Access:https://www.mdpi.com/2218-1989/14/11/602
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