Host phenotype classification from human microbiome data is mainly driven by the presence of microbial taxa.

Abstract excerpt

Machine learning-based classification approaches are widely used to predict host phenotypes from microbiome data. Classifiers are typically employed by considering operational taxonomic units or relative abundance profiles as input features. Such types of data are intrinsically sparse, which opens the opportunity to make predictions from the presence/absence rather than the relative abundance of microbial taxa....

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Bacteria
• Share to Metagenome
• Share to Microbiota