A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles

Tomoya Kitayama, Ayako Kinoshita, Masahiro Sugimoto, Yoichi Nakayama, Masaru Tomita

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Background: In order to improve understanding of metabolic systems there have been attempts to construct S-system models from time courses. Conventionally, non-linear curve-fitting algorithms have been used for modelling, because of the non-linear properties of parameter estimation from time series. However, the huge iterative calculations required have hindered the development of large-scale metabolic pathway models. To solve this problem we propose a novel method involving power-law modelling of metabolic pathways from the Jacobian of the targeted system and the steady-state flux profiles by linearization of S-systems. Results: The results of two case studies modelling a straight and a branched pathway, respectively, showed that our method reduced the number of unknown parameters needing to be estimated. The time-courses simulated by conventional kinetic models and those described by our method behaved similarly under a wide range of perturbations of metabolite concentrations. Conclusion: The proposed method reduces calculation complexity and facilitates the construction of large-scale S-system models of metabolic pathways, realizing a practical application of reverse engineering of dynamic simulation models from the Jacobian of the targeted system and steady-state flux profiles.

Original languageEnglish
Article number24
JournalTheoretical Biology and Medical Modelling
Volume3
DOIs
Publication statusPublished - 2006 Jul 17

ASJC Scopus subject areas

  • Modelling and Simulation
  • Health Informatics

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