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Related Experiment Videos

Metabolic Control Analysis: Separable Matrices and Interdependence of Control Coefficients

Elsner1, Giersch

  • 1Fakultät für Mathematik, Universität Bielefeld, Universitätsstraße, D-33501 Bielefeld, Germany

Journal of Theoretical Biology
|September 29, 1998
PubMed
Summary

The Jacobian inverse (H-1) of metabolic pathways is semi-separable, simplifying control coefficient calculations. This property, related to vanishing two-minors, aids in assessing metabolic control dependencies.

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Area of Science:

  • Biochemistry
  • Systems Biology
  • Mathematical Biology

Background:

  • Control coefficients quantify metabolic pathway regulation.
  • The Jacobian matrix (H) and its inverse (H-1) are crucial for analyzing control coefficient interdependence.
  • For simple metabolic chains, H is tridiagonal, and H-1 exhibits semi-separability.

Purpose of the Study:

  • To explore the mathematical properties of control coefficient matrices in metabolic pathways.
  • To leverage the semi-separable nature of the Jacobian inverse for understanding metabolic control.
  • To develop methods for assessing dependencies within metabolic control coefficients.

Main Methods:

  • Analysis of matrix properties, specifically semi-separability and separability.
  • Investigation of the Jacobian inverse (H-1) of metabolic pathways.

Related Experiment Videos

  • Examination of flux control coefficient (CJ) and concentration control coefficient (Cs) matrices.
  • Graphical construction of regions of vanishing two-minors.
  • Main Results:

    • The inverse Jacobian (H-1) of a metabolic pathway is semi-separable.
    • Flux control coefficient matrix (CJ) is separable; concentration control coefficient matrix (Cs) is semi-separable.
    • Feedback loops can disrupt the semi-separability of Cs by creating new regions of vanishing two-minors.
    • A graphical method is provided to identify these regions.

    Conclusions:

    • The (semi-)separability property of control coefficient matrices provides a framework for assessing metabolic pathway control dependencies.
    • Understanding matrix properties simplifies the analysis of complex metabolic regulation.
    • This mathematical approach offers insights into the structure of metabolic control.