COPASI

COPASI

Introduction to dynamic modelling

Published in Karthik Raman, An Introduction to Computational Systems Biology, 2021

In addition to the tools, it is also important to mention the BioModels database [15] (http://www.ebi.ac.uk/biomodels/), which hosts hundreds of well-curated dynamic models. The repository provides the curated models in different formats, such as SBML and CellML, as well as model files that can be directly loaded and simulated in tools such as COPASI, Octave, Scilab, and XPP-Aut.

Design of experiments for steady-state system identification with applications in genetic and business network modelinG

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Journal Information

Published in Journal of Industrial and Production Engineering, 2020

Cenny Taslim, Theodore T. Allen, Mario Lauria, Shih-Hsien Tseng

where α₁ = 2.0, α₂ = 0.3, α₃ = 1.2, α₄ = 0.4, Κ₁ = 1.0, Κ₂ = 1.1, Κ₃ = 0.5, Κ₄ = 1.1, с₁₃ = 0.8, с₁₄ = 2.0, ω₁₃₄ = 0.4, q₂₁ = 0.2, q₃₁ = 0.8, and q₄₂ = 1.5. Also, ε1, ε2, ε3, and ε4 are random variables which are assumed to equal zero when plotting mean response values. The above coefficients were selected with some degree of arbitrariness to be representative of coefficients used in the widely referenced COPASI software [2], which also offers a nonlinear test bed but with no concise, transparent description. COPASI (COmplex PAthway SImulator) is the simulation software for modeling and analyzing the biochemical networks field [38].

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Introduction to dynamic modelling

Design of experiments for steady-state system identification with applications in genetic and business network modelinG