F2014.1.2 Copasi
Ontology highlight
ABSTRACT:
SUBMITTER: Andrew Millar
PROVIDER: 660 | FAIRDOMHub | 2019-12-20
REPOSITORIES: FAIRDOMHub
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Project description:Motivation:COPASI is an open source software package for constructing, simulating and analyzing dynamic models of biochemical networks. COPASI is primarily intended to be used with a graphical user interface but often it is desirable to be able to access COPASI features programmatically, with a high level interface. Results:PyCoTools is a Python package aimed at providing a high level interface to COPASI tasks with an emphasis on model calibration. PyCoTools enables the construction of COPASI models and the execution of a subset of COPASI tasks including time courses, parameter scans and parameter estimations. Additional 'composite' tasks which use COPASI tasks as building blocks are available for increasing parameter estimation throughput, performing identifiability analysis and performing model selection. PyCoTools supports exploratory data analysis on parameter estimation data to assist with troubleshooting model calibrations. We demonstrate PyCoTools by posing a model selection problem designed to show case PyCoTools within a realistic scenario. The aim of the model selection problem is to test the feasibility of three alternative hypotheses in explaining experimental data derived from neonatal dermal fibroblasts in response to TGF-? over time. PyCoTools is used to critically analyze the parameter estimations and propose strategies for model improvement. Availability and implementation:PyCoTools can be downloaded from the Python Package Index (PyPI) using the command 'pip install pycotools' or directly from GitHub (https://github.com/CiaranWelsh/pycotools). Documentation at http://pycotools.readthedocs.io. Supplementary information:Supplementary data are available at Bioinformatics online.
| S-EPMC6198863 | biostudies-literature
Project description:MotivationComputational modeling is widely used for deepening the understanding of biological processes. Parameterizing models to experimental data needs computationally efficient techniques for parameter estimation. Challenges for parameter estimation include in general the high dimensionality of the parameter space with local minima and in specific for stochastic modeling the intrinsic stochasticity.ResultsWe implemented the recently suggested multiple shooting for stochastic systems (MSS) objective function for parameter estimation in stochastic models into COPASI. This MSS objective function can be used for parameter estimation in stochastic models but also shows beneficial properties when used for ordinary differential equation models. The method can be applied with all of COPASI's optimization algorithms, and can be used for SBML models as well.Availability and implementationThe methodology is available in COPASI as of version 4.15.95 and can be downloaded from http://www.copasi.orgContactfrank.bergmann@bioquant.uni-heidelberg.de or fbergman@caltech.eduSupplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC6169462 | biostudies-literature
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Project description:Kinetic model of extended MEP pathway in wild-type Arabidopsis thaliana.
This model was used for the Parameter Estimation task in COPASI. Reactions for isoprene and cis-abienol synthesis are included but made inactive by setting their k=0. A new Parameter Estimation task can be performed by accesing COPASI/Tasks/Parameter Estimation. Notes about the parameters used in the model can be found in SupplModPar.
More description in
Total optimization potential (TOP) approach based constrained design of isoprene and cis-abienol production in A. thaliana,
Authors: Katrina D. Neiburga, Reinis Muiznieks, Darta M. Zake, Agris Pentjuss, Vitalijs Komasilovs, Johann Rohwer, Alain Tissier, Egils Stalidzans
2023-02-04 | MODEL2206090001 | BioModels
Project description:Kinetic model of extended MEP pathway in Arabidopsis thaliana for cis-abienol production.
This model was used for determining total optimization potential (TOP) of cis-abienol production in Arabidopsis thaliana using Spacescanner (https://github.com/atiselsts/spacescanner). This model was used to make designs A, B and C. An optimization task in COPASI can be perfomed using this model by accesing COPASI/Tasks/Optimization. Parameters which will be changed during the optimization and the optimization constraints can be selected.
More description in
Total optimization potential (TOP) approach based constrained design of isoprene and cis-abienol production in A. thaliana,
Authors: Katrina D. Neiburga, Reinis Muiznieks, Darta M. Zake, Agris Pentjuss, Vitalijs Komasilovs, Johann Rohwer, Alain Tissier, Egils Stalidzans
2023-02-04 | MODEL2206090002 | BioModels