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REDEMPTION: reduced dimension ensemble modeling and parameter estimation.

Liu Y, Manesso E, Gunawan R - Bioinformatics (2015)

Bottom Line: For models with more reactions than measured species, a common scenario in biological modeling, the parameter estimation is formulated as a nested optimization problem based on incremental parameter estimation strategy.REDEMPTION also includes a tool for the identification of an ensemble of parameter combinations that provide satisfactory goodness-of-fit to the data.The functionalities of REDEMPTION are accessible through a MATLAB user interface (UI), as well as through programming script.

View Article: PubMed Central - PubMed

Affiliation: Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zurich, 8093, Zurich, Switzerland and Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.

No MeSH data available.


Workflow of parameter estimation and ensemble generation in REDEMPTION applied to branched pathway example
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btv365-F1: Workflow of parameter estimation and ensemble generation in REDEMPTION applied to branched pathway example

Mentions: Model and data specifications: REDEMPTION’s UI starts with the Main window (Fig. 1a), from which users can access all functionalities. The ODE model equations can be specified manually through the Model Editor using power-law or linear-logarithmic (lin-log) kinetics (Fig. 1c), or by importing an SBML file. In addition, REDEMPTION requires upper and lower bound values for the model parameters. A parameter will be estimated from data when the upper and lower bounds differ. Users also need to provide the time-series concentration data in Comma-Separated Values (CSV) format. For data pre-processing, REDEMPTION includes piecewise polynomial spline-fitting, where users can adjust the number of pieces and the order of polynomials (Fig 1d).Fig. 1.


REDEMPTION: reduced dimension ensemble modeling and parameter estimation.

Liu Y, Manesso E, Gunawan R - Bioinformatics (2015)

Workflow of parameter estimation and ensemble generation in REDEMPTION applied to branched pathway example
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4595898&req=5

btv365-F1: Workflow of parameter estimation and ensemble generation in REDEMPTION applied to branched pathway example
Mentions: Model and data specifications: REDEMPTION’s UI starts with the Main window (Fig. 1a), from which users can access all functionalities. The ODE model equations can be specified manually through the Model Editor using power-law or linear-logarithmic (lin-log) kinetics (Fig. 1c), or by importing an SBML file. In addition, REDEMPTION requires upper and lower bound values for the model parameters. A parameter will be estimated from data when the upper and lower bounds differ. Users also need to provide the time-series concentration data in Comma-Separated Values (CSV) format. For data pre-processing, REDEMPTION includes piecewise polynomial spline-fitting, where users can adjust the number of pieces and the order of polynomials (Fig 1d).Fig. 1.

Bottom Line: For models with more reactions than measured species, a common scenario in biological modeling, the parameter estimation is formulated as a nested optimization problem based on incremental parameter estimation strategy.REDEMPTION also includes a tool for the identification of an ensemble of parameter combinations that provide satisfactory goodness-of-fit to the data.The functionalities of REDEMPTION are accessible through a MATLAB user interface (UI), as well as through programming script.

View Article: PubMed Central - PubMed

Affiliation: Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zurich, 8093, Zurich, Switzerland and Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland.

No MeSH data available.