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Disentangling Interactions in the Microbiome: A Network Perspective

Microbiota are now widely recognized as being central players in the health of all organisms and ecosystems, and subsequently have been the subject of intense study. However, analyzing and converting microbiome data into meaningful biological insights remain very challenging. In this review, we high...

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Detalles Bibliográficos
Autores principales: Layeghifard, Mehdi, Hwang, David M., Guttman, David S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7172547/
https://www.ncbi.nlm.nih.gov/pubmed/27916383
http://dx.doi.org/10.1016/j.tim.2016.11.008
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author Layeghifard, Mehdi
Hwang, David M.
Guttman, David S.
author_facet Layeghifard, Mehdi
Hwang, David M.
Guttman, David S.
author_sort Layeghifard, Mehdi
collection PubMed
description Microbiota are now widely recognized as being central players in the health of all organisms and ecosystems, and subsequently have been the subject of intense study. However, analyzing and converting microbiome data into meaningful biological insights remain very challenging. In this review, we highlight recent advances in network theory and their applicability to microbiome research. We discuss emerging graph theoretical concepts and approaches used in other research disciplines and demonstrate how they are well suited for enhancing our understanding of the higher-order interactions that occur within microbiomes. Network-based analytical approaches have the potential to help disentangle complex polymicrobial and microbe–host interactions, and thereby further the applicability of microbiome research to personalized medicine, public health, environmental and industrial applications, and agriculture.
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spelling pubmed-71725472020-04-22 Disentangling Interactions in the Microbiome: A Network Perspective Layeghifard, Mehdi Hwang, David M. Guttman, David S. Trends Microbiol Article Microbiota are now widely recognized as being central players in the health of all organisms and ecosystems, and subsequently have been the subject of intense study. However, analyzing and converting microbiome data into meaningful biological insights remain very challenging. In this review, we highlight recent advances in network theory and their applicability to microbiome research. We discuss emerging graph theoretical concepts and approaches used in other research disciplines and demonstrate how they are well suited for enhancing our understanding of the higher-order interactions that occur within microbiomes. Network-based analytical approaches have the potential to help disentangle complex polymicrobial and microbe–host interactions, and thereby further the applicability of microbiome research to personalized medicine, public health, environmental and industrial applications, and agriculture. Elsevier Ltd. 2017-03 2016-12-01 /pmc/articles/PMC7172547/ /pubmed/27916383 http://dx.doi.org/10.1016/j.tim.2016.11.008 Text en © 2016 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Layeghifard, Mehdi
Hwang, David M.
Guttman, David S.
Disentangling Interactions in the Microbiome: A Network Perspective
title Disentangling Interactions in the Microbiome: A Network Perspective
title_full Disentangling Interactions in the Microbiome: A Network Perspective
title_fullStr Disentangling Interactions in the Microbiome: A Network Perspective
title_full_unstemmed Disentangling Interactions in the Microbiome: A Network Perspective
title_short Disentangling Interactions in the Microbiome: A Network Perspective
title_sort disentangling interactions in the microbiome: a network perspective
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7172547/
https://www.ncbi.nlm.nih.gov/pubmed/27916383
http://dx.doi.org/10.1016/j.tim.2016.11.008
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