RKappa: Statistical Sampling Suite for Kappa Models
We present RKappa, a framework for the development and analysis of rule-based models within a mature, statistically empowered R environment. The infrastructure allows model editing, modification, parameter sampling, simulation, statistical analysis and visualisation without leaving the R environment. We demonstrate its effectiveness through its application to Global Sensitivity Analysis, exploring it in “parallel” and “concurrent” implementations.
The pipeline was designed for high performance computing platforms and aims to facilitate analysis of the behaviour of large-scale systems with limited knowledge of exact mechanisms and respectively sparse availability of parameter values. We illustrate it here with two biological examples. The package is available on github: https://github.com/lptolik/R4Kappa.
KeywordsGlobal Sensitivity Analysis Rule-based modeling Model composition Model analysis
AS was partially supported by RFBR, research project No. 14-44-03679 r_centr_a, and European Research Council (ERC) under grants 320823 RULE. The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement nos. 241498 (EUROSPIN project), 242167 (SynSys-project) and 604102 (Human Brain Project). This work has made use of the resources provided by the Edinburgh Compute and Data Facility (ECDF) (http://www.ecdf.ed.ac.uk/). The ECDF is partially supported by the eDIKT initiative (http://www.edikt.org.uk).
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