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.

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References in zbMATH (referenced in 105 articles , 1 standard article )

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  1. Melgratti, Hernán; Mezzina, Claudio Antares; Pinna, G. Michele: A Petri net view of covalent bonds (2022)
  2. Barbuti, Roberto; Gori, Roberta; Milazzo, Paolo; Nasti, Lucia: A survey of gene regulatory networks modelling methods: from differential equations, to Boolean and qualitative bioinspired models (2020)
  3. Bortolussi, Luca; Hillston, Jane; Loreti, Michele: Fluid approximation of broadcasting systems (2020)
  4. Troják, Matej; Šafránek, David; Brim, Luboš; Šalagovič, Jakub; Červený, Jan: Executable biochemical space for specification and analysis of biochemical systems (2020)
  5. Wright, Thomas; Stark, Ian: Modelling patterns of gene regulation in the bond-calculus (2020)
  6. Boreale, Michele: Algebra, coalgebra, and minimization in polynomial differential equations (2019)
  7. Cardelli, Luca; Tribastone, Mirco; Tschaikowski, Max; Vandin, Andrea: Symbolic computation of differential equivalences (2019)
  8. Júlvez, Jorge; Oliver, Stephen G.: Flexible nets: a modeling formalism for dynamic systems with uncertain parameters (2019)
  9. Sanguinetti, Guido (ed.); Huynh-Thu, Vân Anh (ed.): Gene regulatory networks. Methods and protocols (2019)
  10. Toro, Mauricio: A general overview of formal languages for individual-based modelling of ecosystems (2019)
  11. Baier, Christel; de Alfaro, Luca; Forejt, Vojtěch; Kwiatkowska, Marta: Model checking probabilistic systems (2018)
  12. Aderhold, Andrej; Husmeier, Dirk; Grzegorczyk, Marco: Approximate Bayesian inference in semi-mechanistic models (2017)
  13. Boreale, Michele: Algebra, coalgebra, and minimization in polynomial differential equations (2017)
  14. Giannakis, Konstantinos; Andronikos, Theodore: Membrane automata for modeling biomolecular processes (2017)
  15. Grzegorczyk, Marco; Aderhold, Andrej; Husmeier, Dirk: Targeting Bayes factors with direct-path non-equilibrium thermodynamic integration (2017)
  16. Bortolussi, Luca: Hybrid behaviour of Markov population models (2016)
  17. Bortolussi, Luca; Gast, Nicolas: Mean-field limits beyond ordinary differential equations (2016)
  18. Bortolussi, Luca; Milios, Dimitrios; Sanguinetti, Guido: Smoothed model checking for uncertain continuous-time Markov chains (2016)
  19. Cardelli, Luca; Tribastone, Mirco; Tschaikowski, Max; Vandin, Andrea: Symbolic computation of differential equivalences (2016)
  20. Colvin, Robert J.: Modelling and analysing neural networks using a hybrid process algebra (2016)

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