Literature DB >> 2453282

Stoichiometric network analysis.

B L Clarke1.   

Abstract

Stoichiometric network analysis is a systematic, general approach to the qualitative, nonlinear dynamics of chemical reaction mechanisms and other systems with stoichiometry. The advantage of a qualitative approach is that no rate constants are needed to determine qualitative features of the dynamics. If one is interested in stability, the approach yields inequalities among the steady-state concentrations and the rate of flow through sequences of important reactions. These parameters are often the ones most easily measured experimentally. By comparing such experiments with the inequalities derived from stoichiometric network analysis, one can often prove that certain mechanisms cannot account for oscillations or other types of observed dynamics. The approach covers far more than stability. The existence of steady states of zero concentration has an interesting mathematics and applies to chemical evolution. The folding of the manifold of steady states can be found by direct calculation and plays a role in switching enzymes on and off. The approach leads to theorems showing that some steady states are globally attracting or, possibly, that a region containing chaos or an oscillation is globally attracting. The subject of sensitivity analysis has been reformulated in this context. Algorithms that apply many of the theoretical results to chemical networks have been developed and combined into a computer program package.

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Year:  1988        PMID: 2453282     DOI: 10.1007/bf02918360

Source DB:  PubMed          Journal:  Cell Biophys        ISSN: 0163-4992


  1 in total

1.  Studies in irreversible thermodynamics. IV. Diagrammatic representation of steady state fluxes for unimolecular systems.

Authors:  T L Hill
Journal:  J Theor Biol       Date:  1966-04       Impact factor: 2.691

  1 in total
  26 in total

1.  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

2.  The JAK-STAT signaling network in the human B-cell: an extreme signaling pathway analysis.

Authors:  Jason A Papin; Bernhard O Palsson
Journal:  Biophys J       Date:  2004-07       Impact factor: 4.033

3.  Kinetic constraints for formation of steady states in biochemical networks.

Authors:  Junli Liu
Journal:  Biophys J       Date:  2005-02-24       Impact factor: 4.033

4.  The geometry of the flux cone of a metabolic network.

Authors:  Clemens Wagner; Robert Urbanczik
Journal:  Biophys J       Date:  2005-09-23       Impact factor: 4.033

5.  Model of calcium oscillations due to negative feedback in olfactory cilia.

Authors:  J Reidl; P Borowski; A Sensse; J Starke; M Zapotocky; M Eiswirth
Journal:  Biophys J       Date:  2005-12-02       Impact factor: 4.033

Review 6.  Systems interface biology.

Authors:  Francis J Doyle; Jörg Stelling
Journal:  J R Soc Interface       Date:  2006-10-22       Impact factor: 4.118

7.  Stability of open pathways.

Authors:  Edward H Flach; Santiago Schnell
Journal:  Math Biosci       Date:  2010-09-26       Impact factor: 2.144

8.  Subnetwork analysis reveals dynamic features of complex (bio)chemical networks.

Authors:  Carsten Conradi; Dietrich Flockerzi; Jörg Raisch; Jörg Stelling
Journal:  Proc Natl Acad Sci U S A       Date:  2007-11-27       Impact factor: 11.205

Review 9.  Which metabolic pathways generate and characterize the flux space? A comparison among elementary modes, extreme pathways and minimal generators.

Authors:  Francisco Llaneras; Jesús Picó
Journal:  J Biomed Biotechnol       Date:  2010-05-11

10.  Steady state detection of chemical reaction networks using a simplified analytical method.

Authors:  Ivan Martínez-Forero; Antonio Peláez-López; Pablo Villoslada
Journal:  PLoS One       Date:  2010-06-03       Impact factor: 3.240

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