Modelling and Analysis of the NF-κB Pathway in Bio-PEPA

Ciocchetta, Federica; Degasperi, Andrea; Heath, John K.; Hillston, Jane

doi:10.1007/978-3-642-11712-1_7

Cited by 9 publications

(4 citation statements)

References 40 publications

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“…ODEs (ordinary differential equations) are often used to model the dynamics of biochemical processes, and the availability of supporting tools [2], [3], [4] makes their power more accessible to end users. Tools based on process calculi [5], [6] have been successfully employed in modelling complex biological events [7], [8] as well. However, it is often difficult for a biologist to operate with the modelling formalisms and tools that allow to develop executable biological models, especially because such tools often require theoretical foundations or training that a biologist needs to acquire beforehand.…”

Section: Introductionmentioning

confidence: 99%

Modelling biological pathway dynamics with Timed Automata

Schivo

Scholma

Wanders

et al. 2012

2012 IEEE 12th International Conference on Bioinformatics &Amp; Bioengineering (BIBE)

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When analysing complex interaction networks occurring in biological cells, a biologist needs computational support in order to understand the effects of signalling molecules (e.g. growth factors, drugs). ANIMO (Analysis of Networks with Interactive MOdelling) is a tool that allows the user to create and explore 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 domainspecific language used to represent signalling networks. This enforces precision and uniformity in the definition of signalling pathways, contributing to the integration of signalling event models into complex, crosstalk-driven networks. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic cell behaviour. A user friendly interface makes the use of Timed Automata completely transparent to the biologist, while keeping the expressive power intact. This allows to define relatively simple, yet faithful models of complex biological interactions. The resulting timed behaviour is displayed graphically, allowing for an intuitive and interactive modelling experience.

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Section: Introductionmentioning

confidence: 99%

Modelling biological pathway dynamics with Timed Automata

Schivo

Scholma

Wanders

et al. 2012

2012 IEEE 12th International Conference on Bioinformatics &Amp; Bioengineering (BIBE)

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show abstract

“…Ordinary differential equations (ODEs) are often used to model the dynamics of biochemical processes, and the availability of supporting tools [2]- [4] makes their power accessible to end users. Process calculi are also classified as executable approaches, and tools based on such formalisms have been successfully used in modeling complex biological events [5], [6]. However, most of the existing modeling tools require theoretical foundations or training in mathematics, and this may hamper the widespread creation of in silico models within the biological community.…”

Section: Modeling Biological Pathway Dynamics Withmentioning

confidence: 99%

Modeling Biological Pathway Dynamics With Timed Automata

Schivo

Scholma²,

Wanders

et al. 2014

IEEE J. Biomed. Health Inform.

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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 capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the 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 analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling 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 behavior 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 behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

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“…Bio-PEPA has also been applied to the modelling of many different biological systems including Goldbeter's model of cyclin oscillation [29,25], the Repressilator [28], the NF-κB signalling pathway [27], the MAPK model [35], circadian clocks [1,2], the gp130/JAK/STAT pathway [44] and trafficking of Src in the mammalian cell [38].…”

Section: Semanticsmentioning

confidence: 99%

Hybrid semantics for Bio-PEPA

Galpin

2014

Information and Computation

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This paper investigates the stochastic, continuous and instantaneous (hybrid) modelling of systems defined in Bio-PEPA, a quantitative process algebra for biological modelling. This is achieved by mapping a Bio-PEPA model to a model in stochastic HYPE, a process algebra that models these three behaviour types in a compositional and structured manner. The novel mapping between process algebras provides another method of analysis for Bio-PEPA models and presents the modeller with a well-structured stochastic HYPE model which can itself be easily modified and is only a small constant larger in size than the Bio-PEPA model. The structure of the stochastic HYPE model generated has desirable properties and also gives a general framework for modelling biochemical systems where the advantages of both stochastic and deterministic simulation are required. Thresholds are introduced for each reaction, and when all values are above these thresholds, the reaction is treated deterministically. However, if a relevant value is below a threshold, the reaction is treated stochastically (as are the changes in species quantities as a result of that reaction). It is proved that in the purely deterministic case and in the purely stochastic case, the stochastic HYPE model has the same behaviour as the Bio-PEPA model when considered purely deterministically and purely stochastically, respectively. Furthermore, addition of instantaneous events in the style of Bio-PEPA with events is illustrated, and a proposal for mapping Bio-PEPA with delays (Bio-PEPAd) to stochastic HYPE is presented.

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Modelling and Analysis of the NF-κB Pathway in Bio-PEPA

Cited by 9 publications

References 40 publications

Modelling biological pathway dynamics with Timed Automata

Modelling biological pathway dynamics with Timed Automata

Modeling Biological Pathway Dynamics With Timed Automata

Hybrid semantics for Bio-PEPA

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