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 journalArticle

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

Fingerprint

Metabolic Networks and Pathways
S-system
Pathway
Power Law
Fluxes
Modeling
Curve fitting
Reverse Engineering
Kinetic Model
Dynamic Simulation
Unknown Parameters
Straight
Reverse engineering
Linearization
Parameter Estimation
Dynamic Model
Metabolites
Simulation Model
Time series
Parameter estimation

ASJC Scopus subject areas

  • Health Informatics
  • Medicine(all)

Cite this

A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles. / Kitayama, Tomoya; Kinoshita, Ayako; Sugimoto, Masahiro; Nakayama, Yoichi; Tomita, Masaru.

In: Theoretical Biology and Medical Modelling, Vol. 3, 24, 17.07.2006.

Research output: Contribution to journalArticle

@article{5dc49bb1053a4992b525cc120fb08b5b,
title = "A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles",
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.",
author = "Tomoya Kitayama and Ayako Kinoshita and Masahiro Sugimoto and Yoichi Nakayama and Masaru Tomita",
year = "2006",
month = "7",
day = "17",
doi = "10.1186/1742-4682-3-24",
language = "English",
volume = "3",
journal = "Theoretical Biology and Medical Modelling",
issn = "1742-4682",
publisher = "BioMed Central",

}

TY - JOUR

T1 - A simplified method for power-law modelling of metabolic pathways from time-course data and steady-state flux profiles

AU - Kitayama, Tomoya

AU - Kinoshita, Ayako

AU - Sugimoto, Masahiro

AU - Nakayama, Yoichi

AU - Tomita, Masaru

PY - 2006/7/17

Y1 - 2006/7/17

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=33751418323&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33751418323&partnerID=8YFLogxK

U2 - 10.1186/1742-4682-3-24

DO - 10.1186/1742-4682-3-24

M3 - Article

C2 - 16846504

AN - SCOPUS:33751418323

VL - 3

JO - Theoretical Biology and Medical Modelling

JF - Theoretical Biology and Medical Modelling

SN - 1742-4682

M1 - 24

ER -