Multi-omics analysis identifies potential microbial and metabolite diagnostic biomarkers of bacterial vaginosis.

Apoorva ChallaJ S MarasS NagpalG TripathiB TanejaG KachhawaS SoodB DhawanP AcharyaA D UpadhyayM YadavR SharmaM BajpaiSomesh Gupta

Published in: Journal of the European Academy of Dermatology and Venereology : JEADV (2024)

Application of machine-learning tools to multi-omics datasets aid biomarker discovery with high predictive performance. Metabolome-derived classification models were observed to have superior diagnostic performance in predicting BV than microbiome-based biomarkers.

Keyphrases

machine learning
single cell
deep learning
artificial intelligence
small molecule
rna seq
microbial community
genome wide
high throughput
big data
lps induced
gene expression
climate change