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Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks
BACKGROUND: Detection of central nodes in asymmetrically directed biological networks depends on centrality metrics quantifying individual nodes’ importance in a network. In topological analyses on metabolic networks, various centrality metrics have been mostly applied to metabolite-centric graphs....
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567475/ https://www.ncbi.nlm.nih.gov/pubmed/31195955 http://dx.doi.org/10.1186/s12859-019-2897-z |
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author | Kim, Eun-Youn Ashlock, Daniel Yoon, Sung Ho |
author_facet | Kim, Eun-Youn Ashlock, Daniel Yoon, Sung Ho |
author_sort | Kim, Eun-Youn |
collection | PubMed |
description | BACKGROUND: Detection of central nodes in asymmetrically directed biological networks depends on centrality metrics quantifying individual nodes’ importance in a network. In topological analyses on metabolic networks, various centrality metrics have been mostly applied to metabolite-centric graphs. However, centrality metrics including those not depending on high connections are largely unexplored for directed reaction-centric graphs. RESULTS: We applied directed versions of centrality metrics to directed reaction-centric graphs of microbial metabolic networks. To investigate the local role of a node, we developed a novel metric, cascade number, considering how many nodes are closed off from information flow when a particular node is removed. High modularity and scale-freeness were found in the directed reaction-centric graphs and betweenness centrality tended to belong to densely connected modules. Cascade number and bridging centrality identified cascade subnetworks controlling local information flow and irreplaceable bridging nodes between functional modules, respectively. Reactions highly ranked with bridging centrality and cascade number tended to be essential, compared to reactions that other central metrics detected. CONCLUSIONS: We demonstrate that cascade number and bridging centrality are useful to identify key reactions controlling local information flow in directed reaction-centric graphs of microbial metabolic networks. Knowledge about the local flow connectivity and connections between local modules will contribute to understand how metabolic pathways are assembled. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2897-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6567475 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-65674752019-06-17 Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks Kim, Eun-Youn Ashlock, Daniel Yoon, Sung Ho BMC Bioinformatics Research Article BACKGROUND: Detection of central nodes in asymmetrically directed biological networks depends on centrality metrics quantifying individual nodes’ importance in a network. In topological analyses on metabolic networks, various centrality metrics have been mostly applied to metabolite-centric graphs. However, centrality metrics including those not depending on high connections are largely unexplored for directed reaction-centric graphs. RESULTS: We applied directed versions of centrality metrics to directed reaction-centric graphs of microbial metabolic networks. To investigate the local role of a node, we developed a novel metric, cascade number, considering how many nodes are closed off from information flow when a particular node is removed. High modularity and scale-freeness were found in the directed reaction-centric graphs and betweenness centrality tended to belong to densely connected modules. Cascade number and bridging centrality identified cascade subnetworks controlling local information flow and irreplaceable bridging nodes between functional modules, respectively. Reactions highly ranked with bridging centrality and cascade number tended to be essential, compared to reactions that other central metrics detected. CONCLUSIONS: We demonstrate that cascade number and bridging centrality are useful to identify key reactions controlling local information flow in directed reaction-centric graphs of microbial metabolic networks. Knowledge about the local flow connectivity and connections between local modules will contribute to understand how metabolic pathways are assembled. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2897-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-06-13 /pmc/articles/PMC6567475/ /pubmed/31195955 http://dx.doi.org/10.1186/s12859-019-2897-z Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Kim, Eun-Youn Ashlock, Daniel Yoon, Sung Ho Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks |
title | Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks |
title_full | Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks |
title_fullStr | Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks |
title_full_unstemmed | Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks |
title_short | Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks |
title_sort | identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567475/ https://www.ncbi.nlm.nih.gov/pubmed/31195955 http://dx.doi.org/10.1186/s12859-019-2897-z |
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