  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, and is illustrated here with two biological examples.
  The package is available on github: https://github.com/lptolik/R4Kappa
