A Simple and Fast Algorithm to Obtain All Invariants of a Generalized Petri Net
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Quality assessment, verification, and validation of modeling and simulation applications
WSC '04 Proceedings of the 36th conference on Winter simulation
Systems Biology: Properties of Reconstructed Networks
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An analysis of the Petri net based model of the human body iron homeostasis process
Computational Biology and Chemistry
Automated Trace Analysis of Discrete-Event System Models
IEEE Transactions on Software Engineering
Bio-PEPA: A framework for the modelling and analysis of biological systems
Theoretical Computer Science
QEST '09 Proceedings of the 2009 Sixth International Conference on the Quantitative Evaluation of Systems
Qualitative and Quantitative Analysis of a Bio-PEPA Model of the Gp130/JAK/STAT Signalling Pathway
Transactions on Computational Systems Biology XI
On the analysis of numerical data time series in temporal logic
CMSB'07 Proceedings of the 2007 international conference on Computational methods in systems biology
Petri nets for systems and synthetic biology
SFM'08 Proceedings of the Formal methods for the design of computer, communication, and software systems 8th international conference on Formal methods for computational systems biology
Design and development of software tools for Bio-PEPA
Winter Simulation Conference
Equivalences for a biological process algebra
Theoretical Computer Science
Conservation of Mass Analysis for Bio-PEPA
Electronic Notes in Theoretical Computer Science (ENTCS)
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Verifying that a computational model implements the conceptual model of some dynamic biological phenomena is an important yet non-trivial task. In this paper, we discuss a variety of steps that contribute to this verification process, using the Bio-PEPA process algebra as a modelling language and describing the verification steps that are supported by the Bio-PEPA tool. In particular, we elaborate on both static analysis based on the structure of models and dynamic analysis of generated stochastic simulation traces performed using the Traviando trace analyser. We illustrate the approach with a model of a JAK/STAT signalling pathway.