Bio-PEPA

In this work we present Bio-PEPA, a process algebra for the modelling and the analysis of biochemical networks. It is a modification of PEPA, originally defined for the performanceanalysis of computer systems, in order to handle some features of biological models, suchas stoichiometry and the use of general kinetic laws. Bio-PEPA may be seen as an intermediate, formal, compositional representation of biological systems, on which different kindsof analysis can be carried out. Bio-PEPA is enriched with some notions of equivalence.Specifically, the isomorphism and strong bisimulation for PEPA have been considered andextended to our language. Finally, we show the translation of a biological model into thenew language and we report some analysis results.


References in zbMATH (referenced in 102 articles , 1 standard article )

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  1. Bortolussi, Luca; Hillston, Jane; Loreti, Michele: Fluid approximation of broadcasting systems (2020)
  2. Boreale, Michele: Algebra, coalgebra, and minimization in polynomial differential equations (2019)
  3. Cardelli, Luca; Tribastone, Mirco; Tschaikowski, Max; Vandin, Andrea: Symbolic computation of differential equivalences (2019)
  4. Júlvez, Jorge; Oliver, Stephen G.: Flexible nets: a modeling formalism for dynamic systems with uncertain parameters (2019)
  5. Sanguinetti, Guido (ed.); Huynh-Thu, Vân Anh (ed.): Gene regulatory networks. Methods and protocols (2019)
  6. Toro, Mauricio: A general overview of formal languages for individual-based modelling of ecosystems (2019)
  7. Baier, Christel; de Alfaro, Luca; Forejt, Vojtěch; Kwiatkowska, Marta: Model checking probabilistic systems (2018)
  8. Aderhold, Andrej; Husmeier, Dirk; Grzegorczyk, Marco: Approximate Bayesian inference in semi-mechanistic models (2017)
  9. Boreale, Michele: Algebra, coalgebra, and minimization in polynomial differential equations (2017)
  10. Giannakis, Konstantinos; Andronikos, Theodore: Membrane automata for modeling biomolecular processes (2017)
  11. Grzegorczyk, Marco; Aderhold, Andrej; Husmeier, Dirk: Targeting Bayes factors with direct-path non-equilibrium thermodynamic integration (2017)
  12. Bortolussi, Luca: Hybrid behaviour of Markov population models (2016)
  13. Bortolussi, Luca; Gast, Nicolas: Mean-field limits beyond ordinary differential equations (2016)
  14. Bortolussi, Luca; Milios, Dimitrios; Sanguinetti, Guido: Smoothed model checking for uncertain continuous-time Markov chains (2016)
  15. Cardelli, Luca; Tribastone, Mirco; Tschaikowski, Max; Vandin, Andrea: Symbolic computation of differential equivalences (2016)
  16. Colvin, Robert J.: Modelling and analysing neural networks using a hybrid process algebra (2016)
  17. Děd, T.; Šafránek, D.; Troják, M.; Klement, M.; Šalagovič, J.; Brim, L.: Formal biochemical space with semantics in Kappa and BNGL (2016)
  18. Hillston, Jane: Quantitative analysis of collective adaptive systems (2016)
  19. Olarte, C.; Chiarugi, D.; Falaschi, M.; Hermith, D.: A proof theoretic view of spatial and temporal dependencies in biochemical systems (2016)
  20. Vandin, Andrea; Tribastone, Mirco: Quantitative abstractions for collective adaptive systems (2016)

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Further publications can be found at: http://homepages.inf.ed.ac.uk/jeh/Bio-PEPA/References.html