Probabilistic model checking of complex biological pathways

Heath, J., Kwiatkowska, M., Norman, G. , Parker, D. and Tymchyshyn, O. (2008) Probabilistic model checking of complex biological pathways. Theoretical Computer Science, 391(3), pp. 239-257. (doi: 10.1016/j.tcs.2007.11.013)

Abstract

Probabilistic model checking is a formal verification technique that has been successfully applied to the analysis of systems from a broad range of domains, including security and communication protocols, distributed algorithms and power management. In this paper we illustrate its applicability to a complex biological system: the FGF (Fibroblast Growth Factor) signalling pathway. We give a detailed description of how this case study can be modelled in the probabilistic model checker PRISM, discussing some of the issues that arise in doing so, and show how we can thus examine a rich selection of quantitative properties of this model. We present experimental results for the case study under several different scenarios and provide a detailed analysis, illustrating how this approach can be used to yield a better understanding of the dynamics of the pathway. Finally, we outline a number of exact and approximate techniques to enable the verification of larger and more complex pathways and apply several of them to the FGF case study.

• Item Type: Articles
• Additional Information: Special Issue on Converging Sciences: Informatics and Biology
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Norman, Dr Gethin
• Authors: Heath, J., Kwiatkowska, M., Norman, G., Parker, D., and Tymchyshyn, O.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science; Q Science > QH Natural history > QH301 Biology
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: Theoretical Computer Science
• Journal Abbr.: Theor. comp. sci.
• Publisher: Elsevier
• ISSN: 0304-3975
• Published Online: 29 November 2007