Modeling biological pathway dynamics with timed automata
| Autor: | Paul van der Vet, Marcel Karperien, Stefano Schivo, Brend Wanders, Jetse Scholma, Ricardo A. Urquidi Camacho, Jaco van de Pol, Rom Langerak, Janine N. Post |
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| Přispěvatelé: | Developmental BioEngineering, Databases (Former) |
| Rok vydání: | 2014 |
| Předmět: |
Model checking
Signaling pathways Theoretical computer science Computer science Interface (Java) Models Biological PC12 Cells User-Computer Interface Health Information Management User-friendly Animals Timed Automata Electrical and Electronic Engineering Abstraction (linguistics) Systems Biology computer.file_format Complex network Computer Science Applications Automaton System dynamics Rats Executable computer Biological network Dynamic modeling Biotechnology Signal Transduction |
| Zdroj: | IEEE journal of biomedical and health informatics, 18(3), 832-839. IEEE |
| ISSN: | 2168-2208 2168-2194 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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