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65
Probabilistic model checking of complex biological pathways
, 2006
"... 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 applicab ..."
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Cited by 94 (18 self)
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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. 1
A Programming Language for Composable DNA Circuits
- J. R. SOC INTERFACE
, 2009
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Stochastic Bigraphs
- MFPS 2008
, 2008
"... In this paper we present a stochastic semantics for Bigraphical Reactive Systems. A reduction and a labelled stochastic semantics for bigraphs are defined. As a sanity check, we prove that the two semantics are consistent with each other. We illustrate the expressiveness of the framework with an exa ..."
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Cited by 44 (13 self)
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In this paper we present a stochastic semantics for Bigraphical Reactive Systems. A reduction and a labelled stochastic semantics for bigraphs are defined. As a sanity check, we prove that the two semantics are consistent with each other. We illustrate the expressiveness of the framework with an example of membrane budding in a biological system.
Embedded probabilistic programming
- In Working conf. on domain specific lang
, 2009
"... Abstract. Two general techniques for implementing a domain-specific language (DSL) with less overhead are the finally-tagless embedding of object programs and the direct-style representation of side effects. We use these techniques to build a DSL for probabilistic programming, for expressing countab ..."
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Cited by 34 (3 self)
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Abstract. Two general techniques for implementing a domain-specific language (DSL) with less overhead are the finally-tagless embedding of object programs and the direct-style representation of side effects. We use these techniques to build a DSL for probabilistic programming, for expressing countable probabilistic models and performing exact inference and importance sampling on them. Our language is embedded as an ordinary OCaml library and represents probability distributions as ordinary OCaml programs. We use delimited continuations to reify probabilistic programs as lazy search trees, which inference algorithms may traverse without imposing any interpretive overhead on deterministic parts of a model. We thus take advantage of the existing OCaml implementation to achieve competitive performance and ease of use. Inference algorithms can easily be embedded in probabilistic programs themselves.
Using Probabilistic Model Checking in Systems Biology
"... Probabilistic model checking is a formal verification frame-work for systems which exhibit stochastic behaviour. It has been successfully applied to a wide range of domains, includ-ing security and communication protocols, distributed algo-rithms and power management. In this paper we demon-strate i ..."
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Cited by 25 (0 self)
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Probabilistic model checking is a formal verification frame-work for systems which exhibit stochastic behaviour. It has been successfully applied to a wide range of domains, includ-ing security and communication protocols, distributed algo-rithms and power management. In this paper we demon-strate 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 ex-plain how biological pathways can be modelled in the prob-abilistic model checker PRISM and how this enables the analysis of a rich selection of quantitative properties. 1.
Investigating patterns for the processoriented modelling and simulation of space in complex systems
- in Artificial Life XI
, 2008
"... Complex systems modelling and simulation is becoming increasingly important to numerous disciplines. The CoSMoS project aims to produce a unified infrastructure for modelling and simulating all sorts of complex systems, making use of design patterns and the process-oriented programming model. We pro ..."
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Cited by 16 (14 self)
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Complex systems modelling and simulation is becoming increasingly important to numerous disciplines. The CoSMoS project aims to produce a unified infrastructure for modelling and simulating all sorts of complex systems, making use of design patterns and the process-oriented programming model. We provide a description of CoSMoS and present a case study into the modelling of space in complex systems. We describe how two models – absolute geometric space and relational network space – can be captured using processoriented techniques, and how our models can be refactored to allow efficient, distributed simulation. We identify a number of design, implementation and refactoring patterns that can be applied to future complex systems modelling problems.
Probabilistic Model Checking for Systems Biology
"... Probabilistic model checking is a technique for formally verifying quantitative properties of systems that exhibit stochastic behaviour. In this chapter, we show how this approach can be applied to the study of biological systems such as biochemical reaction networks and signalling pathways. We p ..."
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Cited by 14 (1 self)
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Probabilistic model checking is a technique for formally verifying quantitative properties of systems that exhibit stochastic behaviour. In this chapter, we show how this approach can be applied to the study of biological systems such as biochemical reaction networks and signalling pathways. We present an introduction to the state-of-the-art probabilistic model checking tool PRISM using a case study based on the Fibroblast Growth Factor (FGF) signalling pathway.
O.: Refining dynamics of gene regulatory networks in a stochastic π-calculus framework
- In: Transactions on Computational Systems Biology XIII
, 2011
"... Abstract. In this paper, we introduce a framework allowing to model and analyse efficiently Gene Regulatory Networks in their temporal and stochastic aspects. The analysis of stable states and inference of René Thomas ’ discrete parameters derives from this logical formalism. We offer a compositiona ..."
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Cited by 12 (9 self)
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Abstract. In this paper, we introduce a framework allowing to model and analyse efficiently Gene Regulatory Networks in their temporal and stochastic aspects. The analysis of stable states and inference of René Thomas ’ discrete parameters derives from this logical formalism. We offer a compositional approach which comes with a natural translation to the Stochastic π-Calculus. The method we propose consists in successive refinements of generalized dynamics of Gene Regulatory Networks. We apply this method to the control of the differentiation in a Gene Regulatory Network generalizing metazoan segmentation processes. 1
An abstract machine for the stochastic bioambient calculus
- Electronic Notes in Theoretical Computer Science
, 2009
"... This paper presents an abstract machine for the stochastic bioambient calculus. The abstract machine is proved sound and complete with respect to a novel stochastic semantics, and is also shown to preserve the reduction probabilities of the calculus. The machine is implemented as an extension to an ..."
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Cited by 12 (4 self)
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This paper presents an abstract machine for the stochastic bioambient calculus. The abstract machine is proved sound and complete with respect to a novel stochastic semantics, and is also shown to preserve the reduction probabilities of the calculus. The machine is implemented as an extension to an existing simulator for stochastic pi-calculus. Keywords: abstract machine, stochastic, bioambient calculus, correctness, implementation.
