Machine Learning and Artificial Intelligence in the Multi-Omics Approach to Gut Microbiota
University of Naples Federico II · Federico II University Hospital
Abstract
The gut microbiome is involved in human health and disease, and its comprehensive understanding is necessary to exploit it as a diagnostic or therapeutic tool. Multi-omics approaches, including metagenomics, metatranscriptomics, metabolomics, and metaproteomics, enable depiction of the gut microbial ecosystem's complexity. However, these tools generate a large data stream in which integration is needed to produce clinically useful readouts, but, in turn, might be difficult to carry out with conventional statistical methods. Artificial intelligence and machine learning have been increasingly applied to multi-omics datasets in several conditions associated with microbiome disruption, from chronic disorders to…
Citation impact
- FWCI
- 38.41
- Percentile
- 100%
- References
- 157
Authors
4Topics & keywords
- Gut flora
- Artificial intelligence
- Omics
- Computer science
- Computational biology
- Machine learning
- Biology
- Bioinformatics
- Zero hunger
Funding
- ECEuropean Commission
- MDMinistero della SaluteAwards: 5\u00D71000, PNRR\u2013POC\u20132023\u201312377319, GR\u20132018\u201312365734
- MDMinistero dell’Istruzione, dell’Università e della RicercaAward: FIS00001711
- AIAssociazione Italiana per la Ricerca sul CancroAward: 30203
- FRFondazione Roma
- MDMinistero dell'Università e della RicercaAward: RBFR13EWWI_001
- NINational Institutes of HealthAward: 1U01CA230551
- H2Horizon 2020 Framework Programme
- EREuropean Research Council
- NCNational Cancer Institute