Mapping the microbial interactome: Statistical and experimental approaches for microbiome network inference.

Published

Journal Article (Review)

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.

Full Text

Duke Authors

Cited Authors

  • Dohlman, AB; Shen, X

Published Date

  • April 2019

Published In

Volume / Issue

  • 244 / 6

Start / End Page

  • 445 - 458

PubMed ID

  • 30880449

Pubmed Central ID

  • 30880449

Electronic International Standard Serial Number (EISSN)

  • 1535-3699

International Standard Serial Number (ISSN)

  • 1535-3702

Digital Object Identifier (DOI)

  • 10.1177/1535370219836771

Language

  • eng