Partial Least Squares Discriminant Analysis and Bayesian Networks for Metabolomic Prediction of Childhood Asthma

Partial Least Squares Discriminant Analysis and Bayesian Networks for Metabolomic Prediction of Childhood Asthma

To explore novel methods for the analysis of metabolomics data, we compared the ability of Partial Least Squares Discriminant Analysis (PLS-DA) and Bayesian networks (BN) to build predictive plasma metabolite models of age three asthma status in 411 three year olds (<i>n</i> = 59 cases a...

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Bibliographic Details
Main Authors: Rachel S. Kelly, Michael J. McGeachie, Kathleen A. Lee-Sarwar, Priyadarshini Kachroo, Su H. Chu, Yamini V. Virkud, Mengna Huang, Augusto A. Litonjua, Scott T. Weiss, Jessica Lasky-Su
Format: Article
Language:English
Published: MDPI AG 2018-10-01
Series:Metabolites
Subjects:
Partial Least-Squares Discriminant analysis
Bayesian networks
asthma
arginine metabolism
overfitting
Online Access:https://www.mdpi.com/2218-1989/8/4/68

Internet

https://www.mdpi.com/2218-1989/8/4/68

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