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Top-Down Analysis of Temporal Hierarchy in Biochemical Reaction Networks
The study of dynamic functions of large-scale biological networks has intensified in recent years. A critical component in developing an understanding of such dynamics involves the study of their hierarchical organization. We investigate the temporal hierarchy in biochemical reaction networks focusi...
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2518853/ https://www.ncbi.nlm.nih.gov/pubmed/18787685 http://dx.doi.org/10.1371/journal.pcbi.1000177 |
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author | Jamshidi, Neema Palsson, Bernhard Ø. |
author_facet | Jamshidi, Neema Palsson, Bernhard Ø. |
author_sort | Jamshidi, Neema |
collection | PubMed |
description | The study of dynamic functions of large-scale biological networks has intensified in recent years. A critical component in developing an understanding of such dynamics involves the study of their hierarchical organization. We investigate the temporal hierarchy in biochemical reaction networks focusing on: (1) the elucidation of the existence of “pools” (i.e., aggregate variables) formed from component concentrations and (2) the determination of their composition and interactions over different time scales. To date the identification of such pools without prior knowledge of their composition has been a challenge. A new approach is developed for the algorithmic identification of pool formation using correlations between elements of the modal matrix that correspond to a pair of concentrations and how such correlations form over the hierarchy of time scales. The analysis elucidates a temporal hierarchy of events that range from chemical equilibration events to the formation of physiologically meaningful pools, culminating in a network-scale (dynamic) structure–(physiological) function relationship. This method is validated on a model of human red blood cell metabolism and further applied to kinetic models of yeast glycolysis and human folate metabolism, enabling the simplification of these models. The understanding of temporal hierarchy and the formation of dynamic aggregates on different time scales is foundational to the study of network dynamics and has relevance in multiple areas ranging from bacterial strain design and metabolic engineering to the understanding of disease processes in humans. |
format | Text |
id | pubmed-2518853 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-25188532008-09-12 Top-Down Analysis of Temporal Hierarchy in Biochemical Reaction Networks Jamshidi, Neema Palsson, Bernhard Ø. PLoS Comput Biol Research Article The study of dynamic functions of large-scale biological networks has intensified in recent years. A critical component in developing an understanding of such dynamics involves the study of their hierarchical organization. We investigate the temporal hierarchy in biochemical reaction networks focusing on: (1) the elucidation of the existence of “pools” (i.e., aggregate variables) formed from component concentrations and (2) the determination of their composition and interactions over different time scales. To date the identification of such pools without prior knowledge of their composition has been a challenge. A new approach is developed for the algorithmic identification of pool formation using correlations between elements of the modal matrix that correspond to a pair of concentrations and how such correlations form over the hierarchy of time scales. The analysis elucidates a temporal hierarchy of events that range from chemical equilibration events to the formation of physiologically meaningful pools, culminating in a network-scale (dynamic) structure–(physiological) function relationship. This method is validated on a model of human red blood cell metabolism and further applied to kinetic models of yeast glycolysis and human folate metabolism, enabling the simplification of these models. The understanding of temporal hierarchy and the formation of dynamic aggregates on different time scales is foundational to the study of network dynamics and has relevance in multiple areas ranging from bacterial strain design and metabolic engineering to the understanding of disease processes in humans. Public Library of Science 2008-09-12 /pmc/articles/PMC2518853/ /pubmed/18787685 http://dx.doi.org/10.1371/journal.pcbi.1000177 Text en Jamshidi, Palsson. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Jamshidi, Neema Palsson, Bernhard Ø. Top-Down Analysis of Temporal Hierarchy in Biochemical Reaction Networks |
title | Top-Down Analysis of Temporal Hierarchy in Biochemical Reaction Networks |
title_full | Top-Down Analysis of Temporal Hierarchy in Biochemical Reaction Networks |
title_fullStr | Top-Down Analysis of Temporal Hierarchy in Biochemical Reaction Networks |
title_full_unstemmed | Top-Down Analysis of Temporal Hierarchy in Biochemical Reaction Networks |
title_short | Top-Down Analysis of Temporal Hierarchy in Biochemical Reaction Networks |
title_sort | top-down analysis of temporal hierarchy in biochemical reaction networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2518853/ https://www.ncbi.nlm.nih.gov/pubmed/18787685 http://dx.doi.org/10.1371/journal.pcbi.1000177 |
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