Machine learning approaches in microbiome research: challenges and best practices

Machine learning approaches in microbiome research: challenges and best practices

Microbiome data predictive analysis within a machine learning (ML) workflow presents numerous domain-specific challenges involving preprocessing, feature selection, predictive modeling, performance estimation, model interpretation, and the extraction of biological information from the results. To as...

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Bibliographic Details
Main Authors: Georgios Papoutsoglou, Sonia Tarazona, Marta B. Lopes, Thomas Klammsteiner, Eliana Ibrahimi, Julia Eckenberger, Pierfrancesco Novielli, Alberto Tonda, Andrea Simeon, Rajesh Shigdel, Stéphane Béreux, Giacomo Vitali, Sabina Tangaro, Leo Lahti, Andriy Temko, Marcus J. Claesson, Magali Berland
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-09-01
Series:Frontiers in Microbiology
Subjects:
microbiome data analysis
machine learning methods
preprocessing
feature selection
predictive modeling
model selection
Online Access:https://www.frontiersin.org/articles/10.3389/fmicb.2023.1261889/full

Internet

https://www.frontiersin.org/articles/10.3389/fmicb.2023.1261889/full

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