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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2017
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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. |
format | Online Article Text |
id | pubmed-7172547 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
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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