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Strengthening Insights in Microbial Ecological Networks from Theory to Applications
Networks encode the interactions between the components in complex systems and play an essential role in understanding complex systems. Microbial ecological networks provide a system-level insight for comprehensively understanding complex microbial interactions, which play important roles in microbi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Society for Microbiology
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6529547/ https://www.ncbi.nlm.nih.gov/pubmed/31117020 http://dx.doi.org/10.1128/mSystems.00124-19 |
_version_ | 1783420415926861824 |
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author | Lv, Xiaofei Zhao, Kankan Xue, Ran Liu, Yuanhui Xu, Jianming Ma, Bin |
author_facet | Lv, Xiaofei Zhao, Kankan Xue, Ran Liu, Yuanhui Xu, Jianming Ma, Bin |
author_sort | Lv, Xiaofei |
collection | PubMed |
description | Networks encode the interactions between the components in complex systems and play an essential role in understanding complex systems. Microbial ecological networks provide a system-level insight for comprehensively understanding complex microbial interactions, which play important roles in microbial community assembly. However, microbial ecological networks are in their infancy of both network inference and biological interpretation. In this perspective, we articulate the theory gaps and limitations in building and interpreting microbial ecological networks, emphasize developing tools for evaluating the predicted microbial interaction relationships, and predict the potential applications of microbial ecological networks in the long run. |
format | Online Article Text |
id | pubmed-6529547 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Society for Microbiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-65295472019-05-28 Strengthening Insights in Microbial Ecological Networks from Theory to Applications Lv, Xiaofei Zhao, Kankan Xue, Ran Liu, Yuanhui Xu, Jianming Ma, Bin mSystems Perspective Networks encode the interactions between the components in complex systems and play an essential role in understanding complex systems. Microbial ecological networks provide a system-level insight for comprehensively understanding complex microbial interactions, which play important roles in microbial community assembly. However, microbial ecological networks are in their infancy of both network inference and biological interpretation. In this perspective, we articulate the theory gaps and limitations in building and interpreting microbial ecological networks, emphasize developing tools for evaluating the predicted microbial interaction relationships, and predict the potential applications of microbial ecological networks in the long run. American Society for Microbiology 2019-05-21 /pmc/articles/PMC6529547/ /pubmed/31117020 http://dx.doi.org/10.1128/mSystems.00124-19 Text en Copyright © 2019 Lv et al. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Perspective Lv, Xiaofei Zhao, Kankan Xue, Ran Liu, Yuanhui Xu, Jianming Ma, Bin Strengthening Insights in Microbial Ecological Networks from Theory to Applications |
title | Strengthening Insights in Microbial Ecological Networks from Theory to Applications |
title_full | Strengthening Insights in Microbial Ecological Networks from Theory to Applications |
title_fullStr | Strengthening Insights in Microbial Ecological Networks from Theory to Applications |
title_full_unstemmed | Strengthening Insights in Microbial Ecological Networks from Theory to Applications |
title_short | Strengthening Insights in Microbial Ecological Networks from Theory to Applications |
title_sort | strengthening insights in microbial ecological networks from theory to applications |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6529547/ https://www.ncbi.nlm.nih.gov/pubmed/31117020 http://dx.doi.org/10.1128/mSystems.00124-19 |
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