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Comparison on extreme pathways reveals nature of different biological processes

BACKGROUND: Constraint-based reconstruction and analysis (COBRA) is used for modeling genome-scale metabolic networks (MNs). In a COBRA model, extreme pathways (ExPas) are the edges of its conical solution space, which is formed by all viable steady-state flux distributions. ExPa analysis has been s...

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Autores principales: Xi, Yanping, Zhao, Yue, Wang, Li, Wang, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4080357/
https://www.ncbi.nlm.nih.gov/pubmed/24565046
http://dx.doi.org/10.1186/1752-0509-8-S1-S10
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author Xi, Yanping
Zhao, Yue
Wang, Li
Wang, Fei
author_facet Xi, Yanping
Zhao, Yue
Wang, Li
Wang, Fei
author_sort Xi, Yanping
collection PubMed
description BACKGROUND: Constraint-based reconstruction and analysis (COBRA) is used for modeling genome-scale metabolic networks (MNs). In a COBRA model, extreme pathways (ExPas) are the edges of its conical solution space, which is formed by all viable steady-state flux distributions. ExPa analysis has been successfully applied to MNs to reveal their phenotypic capabilities and properties. Recently, the COBRA framework has been extended to transcriptional regulatory networks (TRNs) and transcriptional and translational networks (TTNs), so efforts are needed to determine whether ExPa analysis is also effective on these two types of networks. RESULTS: In this paper, the ExPas resulting from the COBRA models of E.coli's MN, TRN and TTN were horizontally compared from 5 aspects: (1) Total number and the ratio of their amount to reaction amount; (2) Length distribution; (3) Reaction participation; (4) Correlated reaction sets (CoSets); (5) interconnectivity degree. Significant discrepancies in above properties were observed during the comparison, which reveals the biological natures of different biological processes. Besides, by demonstrating the application of ExPa analysis on E.coli, we provide a practical guidance of an improved approach to compute ExPas on COBRA models of TRNs. CONCLUSIONS: ExPas of E.coli's MN, TRN and TTN have different properties, which are strongly connected with various biological natures of biochemical networks, such as topological structure, specificity and redundancy. Our study shows that ExPas are biologically meaningful on the newborn models and suggests the effectiveness of ExPa analysis on them.
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spelling pubmed-40803572014-07-14 Comparison on extreme pathways reveals nature of different biological processes Xi, Yanping Zhao, Yue Wang, Li Wang, Fei BMC Syst Biol Proceedings BACKGROUND: Constraint-based reconstruction and analysis (COBRA) is used for modeling genome-scale metabolic networks (MNs). In a COBRA model, extreme pathways (ExPas) are the edges of its conical solution space, which is formed by all viable steady-state flux distributions. ExPa analysis has been successfully applied to MNs to reveal their phenotypic capabilities and properties. Recently, the COBRA framework has been extended to transcriptional regulatory networks (TRNs) and transcriptional and translational networks (TTNs), so efforts are needed to determine whether ExPa analysis is also effective on these two types of networks. RESULTS: In this paper, the ExPas resulting from the COBRA models of E.coli's MN, TRN and TTN were horizontally compared from 5 aspects: (1) Total number and the ratio of their amount to reaction amount; (2) Length distribution; (3) Reaction participation; (4) Correlated reaction sets (CoSets); (5) interconnectivity degree. Significant discrepancies in above properties were observed during the comparison, which reveals the biological natures of different biological processes. Besides, by demonstrating the application of ExPa analysis on E.coli, we provide a practical guidance of an improved approach to compute ExPas on COBRA models of TRNs. CONCLUSIONS: ExPas of E.coli's MN, TRN and TTN have different properties, which are strongly connected with various biological natures of biochemical networks, such as topological structure, specificity and redundancy. Our study shows that ExPas are biologically meaningful on the newborn models and suggests the effectiveness of ExPa analysis on them. BioMed Central 2014-01-24 /pmc/articles/PMC4080357/ /pubmed/24565046 http://dx.doi.org/10.1186/1752-0509-8-S1-S10 Text en Copyright © 2014 Xi et al.; 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 cited. 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 Proceedings
Xi, Yanping
Zhao, Yue
Wang, Li
Wang, Fei
Comparison on extreme pathways reveals nature of different biological processes
title Comparison on extreme pathways reveals nature of different biological processes
title_full Comparison on extreme pathways reveals nature of different biological processes
title_fullStr Comparison on extreme pathways reveals nature of different biological processes
title_full_unstemmed Comparison on extreme pathways reveals nature of different biological processes
title_short Comparison on extreme pathways reveals nature of different biological processes
title_sort comparison on extreme pathways reveals nature of different biological processes
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4080357/
https://www.ncbi.nlm.nih.gov/pubmed/24565046
http://dx.doi.org/10.1186/1752-0509-8-S1-S10
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