Literature DB >> 22940237

Restricted cooperative games on metabolic networks reveal functionally important reactions.

Max Sajitz-Hermstein1, Zoran Nikoloski.   

Abstract

Understanding the emerging properties of complex biological systems is in the crux of systems biology studies. Computational methods for elucidating the role of each component in the synergetic interplay can be used to identify targets for genetic and metabolic engineering. In particular, we aim at determining the importance of reactions in a metabolic network with respect to a specific biological function. Therefore, we propose a novel game-theoretic framework which integrates restricted cooperative games with the outcome of flux balance analysis. We define productivity games on metabolic networks and present an analysis of their unrestricted and restricted variants based on the game-theoretic solution concept of the Shapley value. Correspondingly, this concept provides a characterization of the robustness and functional centrality for each enzyme involved in a given metabolic network. Furthermore, the comparison of two different environments - feast and famine - demonstrates the dependence of the results on the imposed flux capacities.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 22940237     DOI: 10.1016/j.jtbi.2012.08.018

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  6 in total

1.  Functional centrality as a predictor of shifts in metabolic flux states.

Authors:  Max Sajitz-Hermstein; Zoran Nikoloski
Journal:  BMC Res Notes       Date:  2016-06-21

Review 2.  Computational strategies for a system-level understanding of metabolism.

Authors:  Paolo Cazzaniga; Chiara Damiani; Daniela Besozzi; Riccardo Colombo; Marco S Nobile; Daniela Gaglio; Dario Pescini; Sara Molinari; Giancarlo Mauri; Lilia Alberghina; Marco Vanoni
Journal:  Metabolites       Date:  2014-11-24

3.  An application of the Shapley value to the analysis of co-expression networks.

Authors:  Giulia Cesari; Encarnación Algaba; Stefano Moretti; Juan A Nepomuceno
Journal:  Appl Netw Sci       Date:  2018-08-24

4.  Flux-based hierarchical organization of Escherichia coli's metabolic network.

Authors:  Semidán Robaina-Estévez; Zoran Nikoloski
Journal:  PLoS Comput Biol       Date:  2020-04-20       Impact factor: 4.475

5.  The network organization of protein interactions in the spliceosome is reproduced by the simple rules of food-web models.

Authors:  Mathias M Pires; Maurício Cantor; Paulo R Guimarães; Marcus A M de Aguiar; Sérgio F Dos Reis; Patricia P Coltri
Journal:  Sci Rep       Date:  2015-10-07       Impact factor: 4.379

6.  Structural control of metabolic flux.

Authors:  Max Sajitz-Hermstein; Zoran Nikoloski
Journal:  PLoS Comput Biol       Date:  2013-12-19       Impact factor: 4.475

  6 in total

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