Towards modular verification of pathways: fairness and assumptions

Peter Drábik
(IIT-CNR)
Andrea Maggiolo-Schettini
(University of Pisa)
Paolo Milazzo
(University of Pisa)

Modular verification is a technique used to face the state explosion problem often encountered in the verification of properties of complex systems such as concurrent interactive systems. The modular approach is based on the observation that properties of interest often concern a rather small portion of the system. As a consequence, reduced models can be constructed which approximate the overall system behaviour thus allowing more efficient verification.

Biochemical pathways can be seen as complex concurrent interactive systems. Consequently, verification of their properties is often computationally very expensive and could take advantage of the modular approach.

In this paper we report preliminary results on the development of a modular verification framework for biochemical pathways. We view biochemical pathways as concurrent systems of reactions competing for molecular resources. A modular verification technique could be based on reduced models containing only reactions involving molecular resources of interest.

For a proper description of the system behaviour we argue that it is essential to consider a suitable notion of fairness, which is a well-established notion in concurrency theory but novel in the field of pathway modelling. We propose a modelling approach that includes fairness and we identify the assumptions under which verification of properties can be done in a modular way.

We prove the correctness of the approach and demonstrate it on the model of the EGF receptor-induced MAP kinase cascade by Schoeberl et al.

In Gabriel Ciobanu: Proceedings 6th Workshop on Membrane Computing and Biologically Inspired Process Calculi (MeCBIC 2012), Newcastle, UK, 8th September 2012, Electronic Proceedings in Theoretical Computer Science 100, pp. 63–81.
Published: 15th November 2012.

ArXived at: https://dx.doi.org/10.4204/EPTCS.100.5 bibtex PDF
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