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'''Biochemical systems theory''' is a [[mathematical model]]ling framework for [[biochemical system]]s, based on ordinary [[differential equation]]s (ODE), in which [[biochemistry|biochemical processes]] are represented using '''power-law''' expansions in the variables of the [[system]].
 
This framework, which became known as Biochemical Systems Theory, has been developed since the 1960s by Michael Savageau and others for the [[systems analysis]] of [[biochemical]] processes.<ref>[http://www.biolchem.qui.uc.pt/curso/BST.htm ''Biochemical Systems Theory''], an introduction.</ref> According to Cornish-Bowden (2007) they "regarded this as a general theory of [[metabolic]] control, which includes both metabolic control analysis and flux-oriented theory as special cases".<ref>Athel Cornish-Bowden, [http://bip.cnrs-mrs.fr/bip10/mcafaq4.htm#sava Metabolic control analysis FAQ], website 18 April 2007.</ref>
 
==Representation==
The dynamics of a species is represented by a differential equation with the structure:
 
<center><math>\frac{dX_i}{dt}=\sum_j \mu_{ij} \cdot \gamma_j \prod_k X_k^{f_{jk}}\,</math></center>
 
where X<sub>i</sub> represents one of the n<sub>d</sub> variables of the model (metabolite concentrations, protein concentrations or levels of gene expression). j represents the n<sub>f</sub> biochemical processes affecting the dynamics of the species. On the other hand, <math>\mu</math><sub>ij</sub> (stoichiometric coefficient), <math>\gamma</math><sub>j</sub> (rate constants) and f<sub>jk</sub> (kinetic orders) are two different kinds of parameters defining the dynamics of the system.
 
The principal difference of [[power-law]] [[Mathematical model|models]] with respect to other ODE models used in biochemical systems is that the kinetic orders can be non-integer numbers. A kinetic order can have even negative value when inhibition is modelled. In this way, power-law models have a higher flexibility to reproduce the non-linearity of biochemical systems.
 
Models using power-law expansions have been used during the last 35 years to model and analyse several kinds of biochemical systems including metabolic networks, genetic networks and recently in cell signalling.
 
==See also==
* [[Dynamical systems]]
* [[Ludwig von Bertalanffy]]
* [[Systems theory]]
 
==References==
{{Reflist}}
 
==Literature==
'''Books:'''
* M.A. Savageau, ''Biochemical systems analysis: a study of function and design in molecular biology'', Reading, MA, Addison–Wesley, 1976.
* E.O. Voit (ed), ''Canonical Nonlinear Modeling. S-System Approach to Understanding Complexity'', Van Nostrand Reinhold, NY, 1991.
* E.O. Voit, ''Computational Analysis of Biochemical Systems. A Practical Guide for Biochemists and Molecular Biologists'', Cambridge University Press, Cambridge, U.K., 2000.
* N.V. Torres and E.O. Voit, ''Pathway Analysis and Optimization in Metabolic Engineering'', Cambridge University Press, Cambridge, U.K., 2002.
 
'''Scientific articles:'''
* M.A. Savageau, ''Biochemical systems analysis: I. Some mathematical properties of the rate law for the component enzymatic reactions'' in: J. Theor. Biol. 25, pp.&nbsp;365–369, 1969.
* M.A. Savageau, ''Development of fractal kinetic theory for enzyme-catalysed reactions and implications for the design of biochemical pathways'' in: Biosystems 47(1-2), pp.&nbsp;9–36, 1998.
* M.R. Atkinson et al., ''Design of gene circuits using power-law models'', in: Cell 113, pp.&nbsp;597–607, 2003.
* F. Alvarez-Vasquez et al., ''Simulation and validation of modelled sphingolipid metabolism in Saccharomyces cerevisiae'', ''Nature'' 27, pp.&nbsp;433(7024), pp.&nbsp;425–30, 2005.
*J. Vera et al., ''Power-Law models of signal transduction pathways'' in:  Cellular Signalling {{doi|10.1016/j.cellsig.2007.01.029}}), 2007.
* Eberhart O. Voit, [http://ase.tufts.edu/chemical/documents/newsWorkshopVoit-saturday.pdf ''Applications of Biochemical Systems Theory''], 2006.
 
==External links==
* [http://www.biolchem.qui.uc.pt/curso/BST.htm Biochemical Systems Theory] an introduction,
* http://web.udl.es/Biomath/PowerLaw/
* [http://www.powerlawmodels.org/ A Web on Power-law Models for Biochemical Systems]
 
{{DEFAULTSORT:Biochemical Systems Theory}}
[[Category:Systems biology]]

Revision as of 02:07, 28 December 2013

30 year-old Entertainer or Range Artist Wesley from Drumheller, really loves vehicle, property developers properties for sale in singapore singapore and horse racing. Finds inspiration by traveling to Works of Antoni Gaudí. Biochemical systems theory is a mathematical modelling framework for biochemical systems, based on ordinary differential equations (ODE), in which biochemical processes are represented using power-law expansions in the variables of the system.

This framework, which became known as Biochemical Systems Theory, has been developed since the 1960s by Michael Savageau and others for the systems analysis of biochemical processes.[1] According to Cornish-Bowden (2007) they "regarded this as a general theory of metabolic control, which includes both metabolic control analysis and flux-oriented theory as special cases".[2]

Representation

The dynamics of a species is represented by a differential equation with the structure:

dXidt=jμijγjkXkfjk

where Xi represents one of the nd variables of the model (metabolite concentrations, protein concentrations or levels of gene expression). j represents the nf biochemical processes affecting the dynamics of the species. On the other hand, μij (stoichiometric coefficient), γj (rate constants) and fjk (kinetic orders) are two different kinds of parameters defining the dynamics of the system.

The principal difference of power-law models with respect to other ODE models used in biochemical systems is that the kinetic orders can be non-integer numbers. A kinetic order can have even negative value when inhibition is modelled. In this way, power-law models have a higher flexibility to reproduce the non-linearity of biochemical systems.

Models using power-law expansions have been used during the last 35 years to model and analyse several kinds of biochemical systems including metabolic networks, genetic networks and recently in cell signalling.

See also

References

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Literature

Books:

  • M.A. Savageau, Biochemical systems analysis: a study of function and design in molecular biology, Reading, MA, Addison–Wesley, 1976.
  • E.O. Voit (ed), Canonical Nonlinear Modeling. S-System Approach to Understanding Complexity, Van Nostrand Reinhold, NY, 1991.
  • E.O. Voit, Computational Analysis of Biochemical Systems. A Practical Guide for Biochemists and Molecular Biologists, Cambridge University Press, Cambridge, U.K., 2000.
  • N.V. Torres and E.O. Voit, Pathway Analysis and Optimization in Metabolic Engineering, Cambridge University Press, Cambridge, U.K., 2002.

Scientific articles:

  • M.A. Savageau, Biochemical systems analysis: I. Some mathematical properties of the rate law for the component enzymatic reactions in: J. Theor. Biol. 25, pp. 365–369, 1969.
  • M.A. Savageau, Development of fractal kinetic theory for enzyme-catalysed reactions and implications for the design of biochemical pathways in: Biosystems 47(1-2), pp. 9–36, 1998.
  • M.R. Atkinson et al., Design of gene circuits using power-law models, in: Cell 113, pp. 597–607, 2003.
  • F. Alvarez-Vasquez et al., Simulation and validation of modelled sphingolipid metabolism in Saccharomyces cerevisiae, Nature 27, pp. 433(7024), pp. 425–30, 2005.
  • J. Vera et al., Power-Law models of signal transduction pathways in: Cellular Signalling 21 year-old Glazier James Grippo from Edam, enjoys hang gliding, industrial property developers in singapore developers in singapore and camping. Finds the entire world an motivating place we have spent 4 months at Alejandro de Humboldt National Park.), 2007.
  • Eberhart O. Voit, Applications of Biochemical Systems Theory, 2006.

External links

  1. Biochemical Systems Theory, an introduction.
  2. Athel Cornish-Bowden, Metabolic control analysis FAQ, website 18 April 2007.