| Literature DB >> 30880449 |
Anders B Dohlman1, Xiling Shen1.
Abstract
IMPACT STATEMENT: This review provides a comprehensive description of experimental and statistical tools used for network analyses of the human gut microbiome. Understanding the system dynamics of microbial interactions may lead to the improvement of therapeutic approaches for managing microbiome-associated diseases. Microbiome network inference tools have been developed and applied to both cross-sectional and longitudinal experimental designs, as well as to multi-omic datasets, with the goal of untangling the complex web of microbe-host, microbe-environmental, and metabolism-mediated microbial interactions. The characterization of these interaction networks may lead to a better understanding of the systems dynamics of the human gut microbiome, augmenting our knowledge of the microbiome's role in human health, and guiding the optimization of effective, precise, and rational therapeutic strategies for managing microbiome-associated disease.Entities:
Keywords: Microbiota; experimental; gut; models; statistics; systems
Mesh:
Year: 2019 PMID: 30880449 PMCID: PMC6547001 DOI: 10.1177/1535370219836771
Source DB: PubMed Journal: Exp Biol Med (Maywood) ISSN: 1535-3699