Highly accurate computation of dynamic sensitivities in metabolic reaction systems by a Taylor series method

DOI10.1016/J.MBS.2011.06.004zbMath1227.92033OpenAlexW2043058907WikidataQ51551925 ScholiaQ51551925MaRDI QIDQ648017

Masaaki Egashira, Michio Iwata, Fumihide Shiraishi

Publication date: 22 November 2011

Published in: Mathematical Biosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.mbs.2011.06.004

zbMATH Keywords

sensitivity analysisTaylor series methodhighly-accurate numerical calculation

Mathematics Subject Classification ID

Dynamical systems in biology (37N25) Kinetics in biochemical problems (pharmacokinetics, enzyme kinetics, etc.) (92C45) General theory for ordinary differential equations (34A99) Software, source code, etc. for problems pertaining to biology (92-04)

Related Items (3)

Generalized Taylor's formula for power fractional derivatives ⋮ Using dynamic sensitivities to characterize metabolic reaction systems ⋮ SoftCADS

Uses Software

• RODAS
• ESSYNS

Cites Work

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• Investigation of the performance of fermentation processes using a mathematical model including effects of metabolic bottleneck and toxic product on cells
• Computation and analysis of time-dependent sensitivities in generalized mass action systems
• Dynamic sensitivities in chaotic dynamical systems
• A Taylor-series solution in Cartesian space to GMA-system equations and its application to initial-value problems
• An efficient method for calculation of dynamic logarithmic gains in biochemical systems theory
• Calculation errors of time-varying flux control coefficients obtained from elasticity coefficients by means of summation and connectivity theorems in metabolic control analysis
• A simple and highly accurate numerical differentiation method for sensitivity analysis of large-scale metabolic reaction systems
• A reliable Taylor series-based computational method for the calculation of dynamic sensitivities in large-scale metabolic reaction systems: algorithm and software evaluation
• Efficient Solution of Nonlinear Ordinary Differential Equations Expressed in S-system Canonical Form
• Integration of sensitivity and bifurcation analysis to detect critical processes in a model combining signalling and cell population dynamics

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