Bio-PEPA for Epidemiological Models
Electronic Notes in Theoretical Computer Science (ENTCS)
Proceedings of the 8th International Conference on Computational Methods in Systems Biology
Electronic Notes in Theoretical Computer Science (ENTCS)
Modelling non-linear crowd dynamics in bio-PEPA
FASE'11/ETAPS'11 Proceedings of the 14th international conference on Fundamental approaches to software engineering: part of the joint European conferences on theory and practice of software
Modelling and analysis of the NF-κB pathway in bio-PEPA
Transactions on Computational Systems Biology XII
Fluid analysis of foraging ants
COORDINATION'12 Proceedings of the 14th international conference on Coordination Models and Languages
Analysing robot swarm decision-making with Bio-PEPA
ANTS'12 Proceedings of the 8th international conference on Swarm Intelligence
Complex functional rates in rule-based languages for biochemistry
Transactions on Computational Systems Biology XIV
A Software Interface Between the Narrative Language and Bio-PEPA
Electronic Notes in Theoretical Computer Science (ENTCS)
Complex Functional Rates in the Modeling of Nano Devices (Extended Abstract)
Electronic Notes in Theoretical Computer Science (ENTCS)
Conservation of Mass Analysis for Bio-PEPA
Electronic Notes in Theoretical Computer Science (ENTCS)
| Hi-index | 0.00 |
Bio-PEPA is a timed process algebra designedspecifically for the description of biological phenomena and theiranalysis through quantitative methods such asstochastic simulation and probabilistic model-checking.Two software tools are available for modelling with Bio-PEPA, theBio-PEPA Workbench and the Bio-PEPA Eclipse Plugin.The Bio-PEPAWorkbench is the research prototype tool which allows us to try outnew language features and new types of analysis through rapidprototyping.The Bio-PEPA Eclipse Plugin is a polished modellingenvironment which targets end-users who wish to do Bio-PEPA modellingsupported by a comprehensive integrated development environment.Bothmodelling tools allow the user to analyse their model both in thediscrete stochastic regime and in the sure continuous regime whilemaintaining only a single source in the Bio-PEPA language.