The PEPA workbench: a tool to support a process algebra-based approach to performance modelling
Proceedings of the 7th international conference on Computer performance evaluation : modelling techniques and tools: modelling techniques and tools
Information Processing Letters
Theoretical Computer Science - Special issue: Computational systems biology
A Calculus of Looping Sequences for Modelling Microbiological Systems
Fundamenta Informaticae - SPECIAL ISSUE ON CONCURRENCY SPECIFICATION AND PROGRAMMING (CS&P 2005) Ruciane-Nide, Poland, 28-30 September 2005
Theoretical Computer Science
Theoretical Computer Science
Model Checking Probabilistic and Stochastic Extensions of the π-Calculus
IEEE Transactions on Software Engineering
Bio-PEPA: A framework for the modelling and analysis of biological systems
Theoretical Computer Science
A survey of Markovian behavioral equivalences
SFM'07 Proceedings of the 7th international conference on Formal methods for performance evaluation
Modelization and simulation of nano devices in nanok calculus
CMSB'07 Proceedings of the 2007 international conference on Computational methods in systems biology
Scalable simulation of cellular signaling networks
APLAS'07 Proceedings of the 5th Asian conference on Programming languages and systems
Probabilistic model checking of complex biological pathways
CMSB'06 Proceedings of the 2006 international conference on Computational Methods in Systems Biology
Transactions on Computational Systems Biology VII
Biochemical reaction rules with constraints
ESOP'11/ETAPS'11 Proceedings of the 20th European conference on Programming languages and systems: part of the joint European conferences on theory and practice of software
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The nano@k calculus is a formalism that models biochemical systems by defining its set of reactions. We study the implementation of nano@k into the Stochastic Pi Machine where biochemical systems are defined by regarding molecules as processes, and deriving the overall behaviour by means of communication rules. Our implementation complies with the stochastic behaviors of systems, thus allowing one to use nano@k as an intelligible front-end for a process-oriented simulator. This study also permits to reuse, in nano@k, the theories and tools already developed for process calculi.