Literature DB >> 3297796

Reducing complexity in metabolic networks: making metabolic meshes manageable.

B O Palsson, A Joshi, S S Ozturk.   

Abstract

The dynamics of complex systems can be effectively analyzed by judicious use of intrinsic time constants. Order of magnitude estimation based on time constants has been used successfully to examine the dynamic behavior of complicated processes. The main goal of this paper is to introduce this approach to the analysis of complex metabolic systems. Time constants and dynamic modes of motion are defined within the context of well-established linear algebra. The order of magnitude estimation is then introduced into the systemic framework. The main goals of the analysis are: to provide improved understanding of biochemical dynamics and their physiological significance, and to yield reduced dynamic models that are physiologically realistic but tractable for practical use.

Mesh:

Year:  1987        PMID: 3297796

Source DB:  PubMed          Journal:  Fed Proc        ISSN: 0014-9446


  11 in total

1.  The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities.

Authors:  J S Edwards; B O Palsson
Journal:  Proc Natl Acad Sci U S A       Date:  2000-05-09       Impact factor: 11.205

2.  The convex basis of the left null space of the stoichiometric matrix leads to the definition of metabolically meaningful pools.

Authors:  Iman Famili; Bernhard O Palsson
Journal:  Biophys J       Date:  2003-07       Impact factor: 4.033

3.  Description and analysis of metabolic connectivity and dynamics in the human red blood cell.

Authors:  Kenneth J Kauffman; John David Pajerowski; Neema Jamshidi; Bernhard O Palsson; Jeremy S Edwards
Journal:  Biophys J       Date:  2002-08       Impact factor: 4.033

Review 4.  Modeling cell signaling networks.

Authors:  Narat J Eungdamrong; Ravi Iyengar
Journal:  Biol Cell       Date:  2004-06       Impact factor: 4.458

5.  The modelling of a primitive 'sustainable' conservative cell.

Authors:  James B Bassingthwaighte
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2001-06       Impact factor: 4.226

6.  Mass action stoichiometric simulation models: incorporating kinetics and regulation into stoichiometric models.

Authors:  Neema Jamshidi; Bernhard Ø Palsson
Journal:  Biophys J       Date:  2010-01-20       Impact factor: 4.033

7.  Structural kinetic modeling of metabolic networks.

Authors:  Ralf Steuer; Thilo Gross; Joachim Selbig; Bernd Blasius
Journal:  Proc Natl Acad Sci U S A       Date:  2006-07-31       Impact factor: 11.205

Review 8.  Computational approaches for translational clinical research in disease progression.

Authors:  Mary F McGuire; Madurai Sriram Iyengar; David W Mercer
Journal:  J Investig Med       Date:  2011-08       Impact factor: 2.895

9.  Top-down analysis of temporal hierarchy in biochemical reaction networks.

Authors:  Neema Jamshidi; Bernhard Ø Palsson
Journal:  PLoS Comput Biol       Date:  2008-09-12       Impact factor: 4.475

10.  Formulating genome-scale kinetic models in the post-genome era.

Authors:  Neema Jamshidi; Bernhard Ø Palsson
Journal:  Mol Syst Biol       Date:  2008-03-04       Impact factor: 11.429

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