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1

Center for Bioinformatics Tuebingen ZBIT, University of Tuebingen, Sand 1, 72076 Tübingen, Germany

2

Systems Biology Research Group, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA



These authors contributed equally to this work.





*

Author to whom correspondence should be addressed.



Abstract The identification of suitable model parameters for biochemical reactions has been recognized as a quite difficult endeavor. Parameter values from literature or experiments can often not directly be combined in complex reaction systems. Nature-inspired optimization techniques can find appropriate sets of parameters that calibrate a model to experimentally obtained time series data. We present SBMLsimulator, a tool that combines the Systems Biology Simulation Core Library for dynamic simulation of biochemical models with the heuristic optimization framework EvA2. SBMLsimulator provides an intuitive graphical user interface with various options as well as a fully-featured command-line interface for large-scale and script-based model simulation and calibration. In a parameter estimation study based on a published model and artificial data we demonstrate the capability of SBMLsimulator to identify parameters. SBMLsimulator is useful for both, the interactive simulation and exploration of the parameter space and for the large-scale model calibration and estimation of uncertain parameter values. View Full-Text

Keywords: Systems Biology Markup Language SBML; ordinary differential equation ODE modeling; simulation; parameter estimation Systems Biology Markup Language SBML; ordinary differential equation ODE modeling; simulation; parameter estimation





Autor: Alexander Dörr 1,†,* , Roland Keller 1,†, Andreas Zell 1 and Andreas Dräger 1,2

Fuente: http://mdpi.com/



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