Towards Probabilistic Model Checking on P Systems Using PRISM

Romero–Campero, Francisco J.; Gheorghe, Marian; Bianco, Luca; Pescini, Dario; Pérez–Jiménez, Mario J.; Ceterchi, Rodica

doi:10.1007/11963516_30

Cited by 24 publications

(20 citation statements)

References 19 publications

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“…17 Recently, it has been also applied to analysis of various biological systems, e.g. ERK/MAPK pathway, 4 FGF signalling pathway, 18 cell cycle in eukaryotes, 19 EGFR pathway, 20 T-cell receptor signaling pathway, 21 cell cycle control, 22 diabetes-cancer signaling network, 23 and genetic Boolean gates. 24,25 Two types of verification approaches are utilised in this paper, a qualitative analysis and a quantitative one.…”

Section: Model Checking Tools Allow Analysing Various Temporal Logic mentioning

confidence: 99%

Qualitative and Quantitative Analysis of Systems and Synthetic Biology Constructs using P Systems

et al. 2014

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Qualitative and quantitative analysis of systems and synthetic biology constructs using P systems. ACS Synthetic Biology, 4 (1): 83-92. AbstractComputational models are perceived as an attractive alternative to mathematical models, e.g. ordinary differential equations. These models incorporate a set of methods for specifying, modelling, testing and simulating biological systems. In addition, they can be analysed using algorithmic techniques, e.g. formal verification. This paper shows how formal verification is utilised in systems and synthetic biology through qualitative vs quantitative analysis. Here, we choose two well known case studies: quorum sensing in P. aeruginosas and pulse generator. The paper reports verification analysis of two systems carried out using some model checking tools, integrated to the

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Section: Model Checking Tools Allow Analysing Various Temporal Logic mentioning

confidence: 99%

Qualitative and Quantitative Analysis of Systems and Synthetic Biology Constructs using P Systems

et al. 2014

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“…Although techniques and data structures exist to minimise the model [14,16,13], in the majority of real applications (especially biological applications) the model remains intractable. Notable successes of standard and probabilistic model checking applied to simplified biological systems include [17,12,18,19]. In particular, in [17] the authors have shown the use of probabilistic model checking for the analysis of the cell cycle in eukaryotes, using a modelling language based on membrane systems and process algebra.…”

Section: Membrane Systems With Peripheral Proteinsmentioning

confidence: 99%

“…Notable successes of standard and probabilistic model checking applied to simplified biological systems include [17,12,18,19]. In particular, in [17] the authors have shown the use of probabilistic model checking for the analysis of the cell cycle in eukaryotes, using a modelling language based on membrane systems and process algebra. Platforms based on membrane systems including model checking have been previously implemented, [20].…”

Section: Membrane Systems With Peripheral Proteinsmentioning

confidence: 99%

“…The detailed explanation of the application of Gillespie's stochastic simulation algorithm [15] to a membrane system with peripheral proteins can be found in [9] and [28]. Similar implementations of the Gillespie algorithm have been already proposed in different models of membrane systems where the algorithm has been specifically adapted and optimized to run in multiple compartments and, for these reasons, referred to as multi-compartment in [17] and [20].…”

Section: Definitionmentioning

confidence: 99%

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Statistical Model Checking of Membrane Systems with Peripheral Proteins: Quantifying the Role of Estrogen in Cellular Mitosis and DNA Damage

Cavaliere

Mazza

Sedwards

2013

Emergence, Complexity and Computation

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Systems biology is a natural application of membrane systems, allowing the analysis of biological systems using the formal technique of model checking.To overcome the intractable model size of typical biological systems, statistical model checking may be used to efficiently estimate the probability of properties of interest with arbitrary levels of confidence. In this chapter we analyse a biological system linked to breast cancer, using statistical model checking (SMC) applied to membrane systems. To do this, we have constructed a computational platform that integrates an SMC library with a stochastic simulator of membrane systems with peripheral proteins. We present the methodology to investigate the role of estrogen in cellular mitosis and DNA damage and we use our statistical model checker to find the most appropriate time-dependent dosage of antagonist that should be used to minimize the uncontrolled replication of abnormal cells.

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“…PRISM is used in [30] to model codon bias, studying a range of quantitative properties of the system. Finally, [31] uses PRISM, in combination with several other tools, to analyse gene expression modelled using P-Systems.…”

Section: Related Workmentioning

confidence: 99%

Quantitative Verification Techniques for Biological Processes

Kwiatkowska

Norman

Parker

2009

Algorithmic Bioprocesses

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Summary. Probabilistic model checking is a formal verification framework for systems which exhibit stochastic behaviour. It has been successfully applied to a wide range of domains, including security and communication protocols, distributed algorithms and power management. In this chapter we demonstrate its applicability to the analysis of biological pathways and show how it can yield a better understanding of the dynamics of these systems. Through a case study of the MAP (Mitogen-Activated Protein) Kinase cascade, we explain how biological pathways can be modelled in the probabilistic model checker PRISM and how this enables the analysis of a rich selection of quantitative properties.

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Towards Probabilistic Model Checking on P Systems Using PRISM

Abstract: Abstract. In this paper it is presented the use of P systems and π-calculus to model interacting molecular entities and how they are translated into a probabilistic and symbolic model checker called PRISM.

Cited by 24 publications

References 19 publications

Qualitative and Quantitative Analysis of Systems and Synthetic Biology Constructs using P Systems

Qualitative and Quantitative Analysis of Systems and Synthetic Biology Constructs using P Systems

Statistical Model Checking of Membrane Systems with Peripheral Proteins: Quantifying the Role of Estrogen in Cellular Mitosis and DNA Damage

Quantitative Verification Techniques for Biological Processes

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