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An analytic approximation of the feasible space of metabolic networks

Assuming a steady-state condition within a cell, metabolic fluxes satisfy an underdetermined linear system of stoichiometric equations. Characterizing the space of fluxes that satisfy such equations along with given bounds (and possibly additional relevant constraints) is considered of utmost import...

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Detalles Bibliográficos
Autores principales: Braunstein, Alfredo, Muntoni, Anna Paola, Pagnani, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5384209/
https://www.ncbi.nlm.nih.gov/pubmed/28382977
http://dx.doi.org/10.1038/ncomms14915
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author Braunstein, Alfredo
Muntoni, Anna Paola
Pagnani, Andrea
author_facet Braunstein, Alfredo
Muntoni, Anna Paola
Pagnani, Andrea
author_sort Braunstein, Alfredo
collection PubMed
description Assuming a steady-state condition within a cell, metabolic fluxes satisfy an underdetermined linear system of stoichiometric equations. Characterizing the space of fluxes that satisfy such equations along with given bounds (and possibly additional relevant constraints) is considered of utmost importance for the understanding of cellular metabolism. Extreme values for each individual flux can be computed with linear programming (as flux balance analysis), and their marginal distributions can be approximately computed with Monte Carlo sampling. Here we present an approximate analytic method for the latter task based on expectation propagation equations that does not involve sampling and can achieve much better predictions than other existing analytic methods. The method is iterative, and its computation time is dominated by one matrix inversion per iteration. With respect to sampling, we show through extensive simulation that it has some advantages including computation time, and the ability to efficiently fix empirically estimated distributions of fluxes.
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spelling pubmed-53842092017-04-23 An analytic approximation of the feasible space of metabolic networks Braunstein, Alfredo Muntoni, Anna Paola Pagnani, Andrea Nat Commun Article Assuming a steady-state condition within a cell, metabolic fluxes satisfy an underdetermined linear system of stoichiometric equations. Characterizing the space of fluxes that satisfy such equations along with given bounds (and possibly additional relevant constraints) is considered of utmost importance for the understanding of cellular metabolism. Extreme values for each individual flux can be computed with linear programming (as flux balance analysis), and their marginal distributions can be approximately computed with Monte Carlo sampling. Here we present an approximate analytic method for the latter task based on expectation propagation equations that does not involve sampling and can achieve much better predictions than other existing analytic methods. The method is iterative, and its computation time is dominated by one matrix inversion per iteration. With respect to sampling, we show through extensive simulation that it has some advantages including computation time, and the ability to efficiently fix empirically estimated distributions of fluxes. Nature Publishing Group 2017-04-06 /pmc/articles/PMC5384209/ /pubmed/28382977 http://dx.doi.org/10.1038/ncomms14915 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Braunstein, Alfredo
Muntoni, Anna Paola
Pagnani, Andrea
An analytic approximation of the feasible space of metabolic networks
title An analytic approximation of the feasible space of metabolic networks
title_full An analytic approximation of the feasible space of metabolic networks
title_fullStr An analytic approximation of the feasible space of metabolic networks
title_full_unstemmed An analytic approximation of the feasible space of metabolic networks
title_short An analytic approximation of the feasible space of metabolic networks
title_sort analytic approximation of the feasible space of metabolic networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5384209/
https://www.ncbi.nlm.nih.gov/pubmed/28382977
http://dx.doi.org/10.1038/ncomms14915
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