Modelling biological pathway dynamics with Timed Automata

Stefano Schivo, Jetse Scholma, B. Wanders, Ricardo A. Urquidi Camacho, P.E. van der Vet, Hermanus Bernardus Johannes Karperien, Romanus Langerak, Jan Cornelis van de Pol, Janine Nicole Post

Research output: Contribution to journalArticle

  • 7 Citations

Abstract

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires to capture their dynamics through computational support and models. ANIMO (Analysis of Networks with Interactive MOdelling) is a tool that enables construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analysed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signalling networks. This enforces precision and uniformity in the definition of signalling pathways, contributing to the integration of isolated signalling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behaviour of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behaviour of the network components is displayed graphically, allowing for an intuitive and interactive modelling experience.
LanguageUndefined
Pages832-839
Number of pages7
JournalIEEE journal of biomedical and health informatics
Volume18
Issue number3
DOIs
StatePublished - May 2014

Keywords

  • EWI-23951
  • signaling pathwaystimed automatadynamic modelinguser-friendly
  • dynamic modeling
  • IR-89544
  • user-friendly
  • Signaling pathways
  • METIS-302555
  • Timed Automata

Cite this

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abstract = "Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires to capture their dynamics through computational support and models. ANIMO (Analysis of Networks with Interactive MOdelling) is a tool that enables construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analysed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signalling networks. This enforces precision and uniformity in the definition of signalling pathways, contributing to the integration of isolated signalling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behaviour of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behaviour of the network components is displayed graphically, allowing for an intuitive and interactive modelling experience.",
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Modelling biological pathway dynamics with Timed Automata. / Schivo, Stefano; Scholma, Jetse; Wanders, B.; Urquidi Camacho, Ricardo A.; van der Vet, P.E.; Karperien, Hermanus Bernardus Johannes; Langerak, Romanus; van de Pol, Jan Cornelis; Post, Janine Nicole.

In: IEEE journal of biomedical and health informatics, Vol. 18, No. 3, 05.2014, p. 832-839.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Modelling biological pathway dynamics with Timed Automata

AU - Schivo,Stefano

AU - Scholma,Jetse

AU - Wanders,B.

AU - Urquidi Camacho,Ricardo A.

AU - van der Vet,P.E.

AU - Karperien,Hermanus Bernardus Johannes

AU - Langerak,Romanus

AU - van de Pol,Jan Cornelis

AU - Post,Janine Nicole

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N2 - Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires to capture their dynamics through computational support and models. ANIMO (Analysis of Networks with Interactive MOdelling) is a tool that enables construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analysed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signalling networks. This enforces precision and uniformity in the definition of signalling pathways, contributing to the integration of isolated signalling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behaviour of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behaviour of the network components is displayed graphically, allowing for an intuitive and interactive modelling experience.

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SN - 2168-2194

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ER -

Schivo S, Scholma J, Wanders B, Urquidi Camacho RA, van der Vet PE, Karperien HBJ et al. Modelling biological pathway dynamics with Timed Automata. IEEE journal of biomedical and health informatics. 2014 May;18(3):832-839. Available from, DOI: 10.1109/JBHI.2013.2292880