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Detection of driver metabolites in the human liver metabolic network using structural controllability analysis
BACKGROUND: Abnormal states in human liver metabolism are major causes of human liver diseases ranging from hepatitis to hepatic tumor. The accumulation in relevant data makes it feasible to derive a large-scale human liver metabolic network (HLMN) and to discover important biological principles or...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4024020/ https://www.ncbi.nlm.nih.gov/pubmed/24885538 http://dx.doi.org/10.1186/1752-0509-8-51 |
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author | Liu, Xueming Pan, Linqiang |
author_facet | Liu, Xueming Pan, Linqiang |
author_sort | Liu, Xueming |
collection | PubMed |
description | BACKGROUND: Abnormal states in human liver metabolism are major causes of human liver diseases ranging from hepatitis to hepatic tumor. The accumulation in relevant data makes it feasible to derive a large-scale human liver metabolic network (HLMN) and to discover important biological principles or drug-targets based on network analysis. Some studies have shown that interesting biological phenomenon and drug-targets could be discovered by applying structural controllability analysis (which is a newly prevailed concept in networks) to biological networks. The exploration on the connections between structural controllability theory and the HLMN could be used to uncover valuable information on the human liver metabolism from a fresh perspective. RESULTS: We applied structural controllability analysis to the HLMN and detected driver metabolites. The driver metabolites tend to have strong ability to influence the states of other metabolites and weak susceptibility to be influenced by the states of others. In addition, the metabolites were classified into three classes: critical, high-frequency and low-frequency driver metabolites. Among the identified 36 critical driver metabolites, 27 metabolites were found to be essential; the high-frequency driver metabolites tend to participate in different metabolic pathways, which are important in regulating the whole metabolic systems. Moreover, we explored some other possible connections between the structural controllability theory and the HLMN, and find that transport reactions and the environment play important roles in the human liver metabolism. CONCLUSION: There are interesting connections between the structural controllability theory and the human liver metabolism: driver metabolites have essential biological functions; the crucial role of extracellular metabolites and transport reactions in controlling the HLMN highlights the importance of the environment in the health of human liver metabolism. |
format | Online Article Text |
id | pubmed-4024020 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40240202014-05-28 Detection of driver metabolites in the human liver metabolic network using structural controllability analysis Liu, Xueming Pan, Linqiang BMC Syst Biol Research Article BACKGROUND: Abnormal states in human liver metabolism are major causes of human liver diseases ranging from hepatitis to hepatic tumor. The accumulation in relevant data makes it feasible to derive a large-scale human liver metabolic network (HLMN) and to discover important biological principles or drug-targets based on network analysis. Some studies have shown that interesting biological phenomenon and drug-targets could be discovered by applying structural controllability analysis (which is a newly prevailed concept in networks) to biological networks. The exploration on the connections between structural controllability theory and the HLMN could be used to uncover valuable information on the human liver metabolism from a fresh perspective. RESULTS: We applied structural controllability analysis to the HLMN and detected driver metabolites. The driver metabolites tend to have strong ability to influence the states of other metabolites and weak susceptibility to be influenced by the states of others. In addition, the metabolites were classified into three classes: critical, high-frequency and low-frequency driver metabolites. Among the identified 36 critical driver metabolites, 27 metabolites were found to be essential; the high-frequency driver metabolites tend to participate in different metabolic pathways, which are important in regulating the whole metabolic systems. Moreover, we explored some other possible connections between the structural controllability theory and the HLMN, and find that transport reactions and the environment play important roles in the human liver metabolism. CONCLUSION: There are interesting connections between the structural controllability theory and the human liver metabolism: driver metabolites have essential biological functions; the crucial role of extracellular metabolites and transport reactions in controlling the HLMN highlights the importance of the environment in the health of human liver metabolism. BioMed Central 2014-05-03 /pmc/articles/PMC4024020/ /pubmed/24885538 http://dx.doi.org/10.1186/1752-0509-8-51 Text en Copyright © 2014 Liu and Pan; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Liu, Xueming Pan, Linqiang Detection of driver metabolites in the human liver metabolic network using structural controllability analysis |
title | Detection of driver metabolites in the human liver metabolic network using structural controllability analysis |
title_full | Detection of driver metabolites in the human liver metabolic network using structural controllability analysis |
title_fullStr | Detection of driver metabolites in the human liver metabolic network using structural controllability analysis |
title_full_unstemmed | Detection of driver metabolites in the human liver metabolic network using structural controllability analysis |
title_short | Detection of driver metabolites in the human liver metabolic network using structural controllability analysis |
title_sort | detection of driver metabolites in the human liver metabolic network using structural controllability analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4024020/ https://www.ncbi.nlm.nih.gov/pubmed/24885538 http://dx.doi.org/10.1186/1752-0509-8-51 |
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