921 research outputs found
Petri nets for systems and synthetic biology
We give a description of a Petri net-based framework for
modelling and analysing biochemical pathways, which uni¯es the qualita-
tive, stochastic and continuous paradigms. Each perspective adds its con-
tribution to the understanding of the system, thus the three approaches
do not compete, but complement each other. We illustrate our approach
by applying it to an extended model of the three stage cascade, which
forms the core of the ERK signal transduction pathway. Consequently
our focus is on transient behaviour analysis. We demonstrate how quali-
tative descriptions are abstractions over stochastic or continuous descrip-
tions, and show that the stochastic and continuous models approximate
each other. Although our framework is based on Petri nets, it can be
applied more widely to other formalisms which are used to model and
analyse biochemical networks
Getting the Priorities Right: Saturation for Prioritised Petri Nets
Prioritised Petri net is a powerful modelling language that often
constitutes the core of even more expressive modelling languages such as
GSPNs (Generalized Stochastic Petri nets). The saturation state space
traversal algorithm has proved to be efficient for non-prioritised
concurrent models. Previous works showed that priorities may be encoded into
the transition relation, but doing so defeats the main idea of saturation by
spoiling the locality of transitions. This paper presents an extension of
saturation to natively handle priorities by considering the priority-related
enabledness of transitions separately, adopting the idea of constrained
saturation. To encode the highest priority of enabled transitions in every
state we introduce edge-valued interval decision diagrams. We show that in
case of Petri nets, this data structure can be constructed offline.
According to preliminary measurements, the proposed solution scales better
than previously known matrix decision diagram-based approaches, paving the
way towards efficient stochastic analysis of GSPNs and the model checking of
prioritised models
StocHy: automated verification and synthesis of stochastic processes
StocHy is a software tool for the quantitative analysis of discrete-time
stochastic hybrid systems (SHS). StocHy accepts a high-level description of
stochastic models and constructs an equivalent SHS model. The tool allows to
(i) simulate the SHS evolution over a given time horizon; and to automatically
construct formal abstractions of the SHS. Abstractions are then employed for
(ii) formal verification or (iii) control (policy, strategy) synthesis. StocHy
allows for modular modelling, and has separate simulation, verification and
synthesis engines, which are implemented as independent libraries. This allows
for libraries to be easily used and for extensions to be easily built. The tool
is implemented in C++ and employs manipulations based on vector calculus, the
use of sparse matrices, the symbolic construction of probabilistic kernels, and
multi-threading. Experiments show StocHy's markedly improved performance when
compared to existing abstraction-based approaches: in particular, StocHy beats
state-of-the-art tools in terms of precision (abstraction error) and
computational effort, and finally attains scalability to large-sized models (12
continuous dimensions). StocHy is available at www.gitlab.com/natchi92/StocHy
A Markov Chain Model Checker
Markov chains are widely used in the context of performance and reliability evaluation of systems of various nature. Model checking of such chains with respect to a given (branching) temporal logic formula has been proposed for both the discrete [17,6] and the continuous time setting [4,8]. In this paper, we describe a prototype model checker for discrete and continuous-time Markov chains, the Erlangen Twente Markov Chain Checker ), where properties are expressed in appropriate extensions of CTL. We illustrate the general bene ts of this approach and discuss the structure of the tool. Furthermore we report on first successful applications of the tool to non-trivial examples, highlighting lessons learned during development and application of )
A modular, qualitative modelling of regulatory networks using Petri nets
International audienceAdvances in high-throughput technologies have enabled the de-lineation of large networks of interactions that control cellular processes. To understand behavioural properties of these complex networks, mathematical and computational tools are required. The multi-valued logical formalism, initially defined by R. Thomas and co-workers, proved well adapted to account for the qualitative knowledge available on regulatory interactions, and also to perform analyses of their dynamical properties. In this context, we present two representations of logical models in terms of Petri nets. In a first step, we briefly show how logical models of regulatory networks can be transposed into standard (place/transition) Petri nets, and discuss the capabilities of such representation. In the second part, we focus on logical regulatory modules and their composition, demonstrating that a high-level Petri net representation greatly facilitates the modelling of interconnected modules. Doing so, we introduce an explicit means to integrate signals from various interconnected modules, taking into account their spatial distribution. This provides a flexible modelling framework to handle regulatory networks that operate at both intra-and intercellular levels. As an illustration, we describe a simplified model of the segment-polarity module involved in the segmentation of the Drosophila embryo
Tools and Algorithms for the Construction and Analysis of Systems
This book is Open Access under a CC BY licence. The LNCS 11427 and 11428 proceedings set constitutes the proceedings of the 25th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2019, which took place in Prague, Czech Republic, in April 2019, held as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2019. The total of 42 full and 8 short tool demo papers presented in these volumes was carefully reviewed and selected from 164 submissions. The papers are organized in topical sections as follows: Part I: SAT and SMT, SAT solving and theorem proving; verification and analysis; model checking; tool demo; and machine learning. Part II: concurrent and distributed systems; monitoring and runtime verification; hybrid and stochastic systems; synthesis; symbolic verification; and safety and fault-tolerant systems
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