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Modelling biological pathway dynamics with Timed Automata

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...

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Main Authors: Schivo, S., Scholma, J., Wanders, B., Camacho, R. A. U., van der Vet, P. E., Karperien, M., Langerak, R., van de Pol, J., Post, J. N.
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Language:English
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creator Schivo, S.
Scholma, J.
Wanders, B.
Camacho, R. A. U.
van der Vet, P. E.
Karperien, M.
Langerak, R.
van de Pol, J.
Post, J. N.
description 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 domain-specific 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.
doi_str_mv 10.1109/BIBE.2012.6399719
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Analytical models
Automata
Biological system modeling
Computational modeling
Data models
dynamic behaviour
Kinetic theory
modelling
signalling pathway
timed automata
title Modelling biological pathway dynamics with Timed Automata
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