Formal Analysis of the Wnt/β-catenin through Statistical Model Checking

Ballarini, Paolo; Gallet, Emmanuelle; Gall, Pascale Le; Manceny, Matthieu

doi:10.1007/978-3-662-45231-8_14

Cited by 4 publications

(4 citation statements)

References 16 publications

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“…So it's a performance study to detect any source of failure. This objective is summarized in a study to evaluate and compare several models of manufacturing systems by selecting the most suitable according to specific pre-selection criteria [64]. Our modeling process combines new formal tools specific to WPTSPN, with those of SPN [63] [64] to formulate a clear and expressive approach to specification, analysis, evaluation, and the checking process.…”

Section: Study Case: Flexible Manufacturing Systemsmentioning

confidence: 99%

FMS-Workflow Modeling Based on P-Timed Stochastic Petri Net

Mesmia,

Barkaoui,

Escheikh

2023

JSEA

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In this paper, we propose astochastic Petri net model P-timed Workflow (WPTSPN) to specify, verify, and analyze a business process (BP) of a Flexible Manufacturing System (FMS). After formalizing the semantics of our model, we illustrate how to verifysome of its properties (reachability, safety, boundedness, liveness, correctness, alive tokens, and security) in the P-Timed context. Next, we validate the relevance of the proposed model with MATLAB simulation through a specific FMS case study. Finally, we use a generalized truncated density function to predict the duration of a token's sojourn (residence) in a timed place with respect to the sequence states of the global FMS workflow.

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Section: Study Case: Flexible Manufacturing Systemsmentioning

confidence: 99%

FMS-Workflow Modeling Based on P-Timed Stochastic Petri Net

Mesmia,

Barkaoui,

Escheikh

2023

JSEA

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“…The main contribution is in extending [JLS13] with new adaptive level algorithms based on branching simulation, and to show that this permits to get a more precise estimate of the rare probability. -In [BGGM14], the authors propose an application of SMC to systems biology. They develop a new logic and new SMC techniques for such systems.…”

Section: Content Of the Sessionmentioning

confidence: 99%

Leveraging Applications of Formal Methods, Verification and Validation. Specialized Techniques and Applications

Larsen

Legay²

2014

Lecture Notes in Computer Science

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“…In computational (systems) biology, model checking approaches have been employed for model verification [ 17 – 32 ], parameter estimation/synthesis [ 33 – 42 ], model construction (i.e. both model parameters and structure/topology) [ 43 , 44 ], and robustness computation (considering various perturbations) [ 39 , 44 – 47 ]; see recent review papers [ 48 – 50 ] for a more detailed description.…”

Section: Introductionmentioning

confidence: 99%

“…They are appropriate for small scale systems where the spatial domain is usually not represented explicitly (e.g. cell cycle [ 23 , 27 , 32 , 36 , 44 , 46 , 51 ], gene expression/regulatory networks [ 20 , 35 , 39 , 52 , 53 ], signalling pathways [ 17 , 22 , 25 , 28 – 30 , 38 , 46 , 54 – 56 ]). These model checking approaches cannot be directly employed to verify either spatial computational models because they do not consider how spatial properties change over time, or multilevel computational models because they do not distinguish between different levels of organization.…”

Section: Introductionmentioning

confidence: 99%

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

Pârvu

Gilbert

2016

PLoS ONE

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Insights gained from multilevel computational models of biological systems can be translated into real-life applications only if the model correctness has been verified first. One of the most frequently employed in silico techniques for computational model verification is model checking. Traditional model checking approaches only consider the evolution of numeric values, such as concentrations, over time and are appropriate for computational models of small scale systems (e.g. intracellular networks). However for gaining a systems level understanding of how biological organisms function it is essential to consider more complex large scale biological systems (e.g. organs). Verifying computational models of such systems requires capturing both how numeric values and properties of (emergent) spatial structures (e.g. area of multicellular population) change over time and across multiple levels of organization, which are not considered by existing model checking approaches. To address this limitation we have developed a novel approximate probabilistic multiscale spatio-temporal meta model checking methodology for verifying multilevel computational models relative to specifications describing the desired/expected system behaviour. The methodology is generic and supports computational models encoded using various high-level modelling formalisms because it is defined relative to time series data and not the models used to generate it. In addition, the methodology can be automatically adapted to case study specific types of spatial structures and properties using the spatio-temporal meta model checking concept. To automate the computational model verification process we have implemented the model checking approach in the software tool Mule (http://mule.modelchecking.org). Its applicability is illustrated against four systems biology computational models previously published in the literature encoding the rat cardiovascular system dynamics, the uterine contractions of labour, the Xenopus laevis cell cycle and the acute inflammation of the gut and lung. Our methodology and software will enable computational biologists to efficiently develop reliable multilevel computational models of biological systems.

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Formal Analysis of the Wnt/β-catenin through Statistical Model Checking

Cited by 4 publications

References 16 publications

FMS-Workflow Modeling Based on P-Timed Stochastic Petri Net

FMS-Workflow Modeling Based on P-Timed Stochastic Petri Net

Leveraging Applications of Formal Methods, Verification and Validation. Specialized Techniques and Applications

A Novel Method to Verify Multilevel Computational Models of Biological Systems Using Multiscale Spatio-Temporal Meta Model Checking

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