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Abstract
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 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.
Original language | English |
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Title of host publication | Hybrid Systems Biology |
Subtitle of host publication | Second International Workshop, HSB 2013, Taormina, Italy, September 2, 2013 and Third International Workshop, HSB 2014, Vienna, Austria, July 23-24, 2014, Revised Selected Papers |
Publisher | Springer |
Number of pages | 15 |
ISBN (Electronic) | 978-3-319-27656-4 |
ISBN (Print) | 978-3-319-27655-7 |
DOIs | |
Publication status | Published - 2014 |
Publication series
Name | Lecture Notes in Computer Science |
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Publisher | Springer International Publishing |
Volume | 7699 |
ISSN (Print) | 0302-9743 |
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