Literature DB >> 17303189

A simple and highly accurate numerical differentiation method for sensitivity analysis of large-scale metabolic reaction systems.

Fumihide Shiraishi1, Shingo Furuta, Takaaki Ishimatsu, Jarin Akhter.   

Abstract

Numerical differentiation is known to be one of the most difficult numerical calculation methods to obtain reliable calculated values at all times. A simple numerical differentiation method using a combination of finite-difference formulas, derived by approximation of Taylor-series equations, is investigated in order to efficiently perform the sensitivity analysis of large-scale metabolic reaction systems. A result of the application to four basic mathematical functions reveals that the use of the eight-point differentiation formula with a non-dimensionalized stepsize close to 0.01 mostly provides more than 14 digits of accuracy in double precision for the numerical derivatives. Moreover, a result of the application to the modified TCA cycle model indicates that the numerical differentiation method gives the calculated values of steady-state metabolite concentrations within a range of round-off error and also makes it possible to transform the Michaelis-Menten equations into the S-system equations having the kinetic orders whose accuracies are mostly more than 14 significant digits. Because of the simple structure of the numerical differentiation formula and its promising high accuracy, it is evident that the present numerical differentiation method is useful for the analysis of large-scale metabolic reaction systems according to the systematic procedure of BST.

Entities:  

Mesh:

Year:  2006        PMID: 17303189     DOI: 10.1016/j.mbs.2006.11.007

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  3 in total

1.  PASMet: a web-based platform for prediction, modelling and analyses of metabolic systems.

Authors:  Kansuporn Sriyudthsak; Ramon Francisco Mejia; Masanori Arita; Masami Yokota Hirai
Journal:  Nucleic Acids Res       Date:  2016-05-12       Impact factor: 16.971

2.  PENDISC: a simple method for constructing a mathematical model from time-series data of metabolite concentrations.

Authors:  Kansuporn Sriyudthsak; Michio Iwata; Masami Yokota Hirai; Fumihide Shiraishi
Journal:  Bull Math Biol       Date:  2014-05-07       Impact factor: 1.758

Review 3.  Mathematical Modeling and Dynamic Simulation of Metabolic Reaction Systems Using Metabolome Time Series Data.

Authors:  Kansuporn Sriyudthsak; Fumihide Shiraishi; Masami Yokota Hirai
Journal:  Front Mol Biosci       Date:  2016-05-03
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.