Overview of data preprocessing for machine learning applications in human microbiome research

Overview of data preprocessing for machine learning applications in human microbiome research

Although metagenomic sequencing is now the preferred technique to study microbiome-host interactions, analyzing and interpreting microbiome sequencing data presents challenges primarily attributed to the statistical specificities of the data (e.g., sparse, over-dispersed, compositional, inter-variab...

Full description

Bibliographic Details
Main Authors: Eliana Ibrahimi, Marta B. Lopes, Xhilda Dhamo, Andrea Simeon, Rajesh Shigdel, Karel Hron, Blaž Stres, Domenica D’Elia, Magali Berland, Laura Judith Marcos-Zambrano
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-10-01
Series:Frontiers in Microbiology
Subjects:
human microbiome
data preprocessing
machine learning
compositionality
normalization
metagenomics data
Online Access:https://www.frontiersin.org/articles/10.3389/fmicb.2023.1250909/full

Internet

https://www.frontiersin.org/articles/10.3389/fmicb.2023.1250909/full

Similar Items