Design and Synthesis of Synchronization Skeletons Using Branching-Time Temporal Logic
Logic of Programs, Workshop
Numerical vs. statistical probabilistic model checking
International Journal on Software Tools for Technology Transfer (STTT)
Model and simulation of Na+/K+ pump phosphorylation in the presence of palytoxin
Computational Biology and Chemistry
A temporal logic to deal with fairness in transition systems
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
Spin model checker, the: primer and reference manual
Spin model checker, the: primer and reference manual
CMSB '08 Proceedings of the 6th International Conference on Computational Methods in Systems Biology
Bio-PEPA: A framework for the modelling and analysis of biological systems
Theoretical Computer Science
PRISM 4.0: verification of probabilistic real-time systems
CAV'11 Proceedings of the 23rd international conference on Computer aided verification
Ymer: a statistical model checker
CAV'05 Proceedings of the 17th international conference on Computer Aided Verification
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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Automatic verification techniques such as Probabilistic Model Checking (PMC) have been successfully applied in the specification and analysis of stochastic systems. Some biological systems show these characteristics, allowing PMC usage in unexpected fields. We present and analyze a probabilistic model for palytoxin toxin (PTX) effects on cell transport systems, structures which exchange ions across the plasma membrane. Several diseases are linked to their irregular behavior and their study could help drug development. The model developed in this work shows that as sodium concentration increases, PTX action enhances, suggesting that individuals with diets high in sodium are more vulnerable to PTX. An opposite effect is observed when the potassium concentration increases. PMC can help significantly in the understanding of how cell transport systems behave, suggesting novel experiments which otherwise might be overlooked by biologists.