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REDEMPTION: reduced dimension ensemble modeling and parameter estimation

Summary: Here, we present REDEMPTION (Reduced Dimension Ensemble Modeling and Parameter estimation), a toolbox for parameter estimation and ensemble modeling of ordinary differential equations (ODEs) using time-series data. For models with more reactions than measured species, a common scenario in b...

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Detalles Bibliográficos
Autores principales: Liu, Yang, Manesso, Erica, Gunawan, Rudiyanto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4595898/
https://www.ncbi.nlm.nih.gov/pubmed/26076722
http://dx.doi.org/10.1093/bioinformatics/btv365
Descripción
Sumario:Summary: Here, we present REDEMPTION (Reduced Dimension Ensemble Modeling and Parameter estimation), a toolbox for parameter estimation and ensemble modeling of ordinary differential equations (ODEs) using time-series data. 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. For computational speed-up, REDEMPTION provides a numerical parallelization option using MATLAB Parallel Computing toolbox. Availability and implementation: REDEMPTION can be downloaded from http://www.cabsel.ethz.ch/tools/redemption. Contact: rudi.gunawan@chem.ethz.ch