Machine-learning analysis of cross-study samples according to the gut microbiome in 12 infant cohorts

Machine-learning analysis of cross-study samples according to the gut microbiome in 12 infant cohorts

ABSTRACTCombining and comparing microbiome data from distinct infant cohorts has been challenging because such data are inherently multidimensional and complex. Here, we used an ensemble of machine-learning (ML) models and studied 16S rRNA amplicon sequencing data from 4,099 gut microbiome samples r...

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Bibliographic Details
Main Authors: Petri Vänni, Mysore V. Tejesvi, Niko Paalanne, Kjersti Aagaard, Gail Ackermann, Carlos A. Camargo, Merete Eggesbø, Kohei Hasegawa, Anne G. Hoen, Margaret R. Karagas, Kaija-Leena Kolho, Martin F. Laursen, Johnny Ludvigsson, Juliette Madan, Dennis Ownby, Catherine Stanton, Jakob Stokholm, Terhi Tapiainen
Format: Article
Language:English
Published: American Society for Microbiology 2023-12-01
Series:mSystems
Subjects:
machine learning
bioinformatics
human microbiome
gut microbiome
random forest
infant
Online Access:https://journals.asm.org/doi/10.1128/msystems.00364-23

Internet

https://journals.asm.org/doi/10.1128/msystems.00364-23

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