257 research outputs found

    Modeling biological systems with delays in Bio-PEPA

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    Delays in biological systems may be used to model events for which the underlying dynamics cannot be precisely observed, or to provide abstraction of some behavior of the system resulting more compact models. In this paper we enrich the stochastic process algebra Bio-PEPA, with the possibility of assigning delays to actions, yielding a new non-Markovian process algebra: Bio-PEPAd. This is a conservative extension meaning that the original syntax of Bio-PEPA is retained and the delay specification which can now be associated with actions may be added to existing Bio-PEPA models. The semantics of the firing of the actions with delays is the delay-as-duration approach, earlier presented in papers on the stochastic simulation of biological systems with delays. These semantics of the algebra are given in the Starting-Terminating style, meaning that the state and the completion of an action are observed as two separate events, as required by delays. Furthermore we outline how to perform stochastic simulation of Bio-PEPAd systems and how to automatically translate a Bio-PEPAd system into a set of Delay Differential Equations, the deterministic framework for modeling of biological systems with delays. We end the paper with two example models of biological systems with delays to illustrate the approach.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005

    Petri Nets for Biologically Motivated Computing

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    Petri nets are a general and well-established model of concurrent and distributed computation and behaviour, including that taking place in biological systems. In this survey paper, we are concerned with intrinsic relationships between Petri nets and two formal models inspired by aspects of the functioning of the living cell: membrane systems and reaction systems. In particular, we are interested in the benefits that can result from establishing strong semantical links between Petri nets and membrane systems and reaction systems. We first discuss Petri nets with localities reflecting the compartmentalisation modelled in membrane systems. Then special attention is given to set-nets, a new Petri net model for reaction systems and their qualitative approach to the investigation of the processes carried out by biochemical reactions taking place in the living cell

    Process Algebra with Layers: Multi-scale Integration Modelling applied to Cancer Therapy

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    We present a novel Process Algebra designed for multi-scale integration modelling: Process Algebra with Layers (PAL). The unique feature of PAL is the modularisation of scale into integrated layers: Object and Population. An Object can represent a molecule, organelle, cell, tissue, organ or any organism. Populations hold specific types of Object, for example, life stages, cell phases and infectious states. The syntax and semantics of this novel language are presented. A PAL model of the multi-scale system of cell growth and damage from cancer treatment is given. This model allows the analysis of different scales of the system. The Object and Population levels give insight into the length of a cell cycle and cell population growth respectively. The PAL model results are compared to wet laboratory survival fractions of cells given different doses of radiation treatment [1]. This comparison shows how PAL can be used to aid in investigations of cancer treatment in systems biology

    A modular, qualitative modelling of regulatory networks using Petri nets

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    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

    An overview of existing modeling tools making use of model checking in the analysis of biochemical networks

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    Model checking is a well-established technique for automaticallyverifying complex systems. Recently, model checkers have appearedin computer tools for the analysis of biochemical (and generegulatory) networks. We survey several such tools to assess thepotential of model checking in computational biology. Next, our overviewfocuses on direct applications of existing model checkers, as well ason algorithms for biochemical network analysis influenced by modelchecking, such as those using binary decision diagrams or Booleansatisfiability solvers. We conclude with advantages and drawbacks ofmodel checking for the analysis of biochemical networks

    Formal Verification of Real-time Systems with Preemptive Scheduling

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    International audienceIn this paper, we propose a method for the verification of timed properties for real-time systems featuring a preemptive scheduling policy: the system, modeled as a scheduling time Petri net, is first translated into a linear hybrid automaton to which it is time-bisimilar. Timed properties can then be verified using HyTech. The efficiency of this approach leans on two major points: first, the translation features a minimization of the number of variables (clocks) of the resulting automaton, which is a critical parameter for the efficiency of the ensuing verification. Second, the translation is performed by an over-approximating algorithm, which is based on Difference Bound Matrix and therefore efficient, that nonetheless produces a time-bisimilar automaton despite the over-approximation. The proposed modeling and verification method are generic enough to account for many scheduling policies. In this paper, we specifically show how to deal with Fixed Priority and Earliest Deadline First policies, with the possibility of using Round-Robin for tasks with the same priority. We have implemented the method and give some experimental results illustrating its efficiency

    Structural simplification of chemical reaction networks preserving deterministic semantics

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    International audienceWe study the structural simplification of chemical reaction networks preserving the deterministic kinetics. We aim at finding simplification rules that can eliminate intermediate molecules while preserving the dynamics of all others. The rules should be valid even though the network is plugged into a bigger context. An example is Michaelis-Menten's simplification rule for enzymatic reactions. In this paper, we present a large class of structural simplification rules for reaction networks that can eliminate intermediate molecules at equilibrium, without assuming that all molecules are at equilibrium, i.e. in a steady state. We prove the correctness of our simplification rules for all contexts that preserve the equilibrium of the eliminated molecules. Finally, we illustrate at a concrete example network from systems biology that our simplification rules may allow to drastically reduce the size of reaction networks in practice

    Acta Cybernetica : Volume 15. Number 3.

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    Representing, reasoning and answering questions about biological pathways - various applications

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    Biological organisms are composed of numerous interconnected biochemical processes. Diseases occur when normal functionality of these processes is disrupted. Thus, understanding these biochemical processes and their interrelationships is a primary task in biomedical research and a prerequisite for diagnosing diseases, and drug development. Scientists studying these processes have identified various pathways responsible for drug metabolism, and signal transduction, etc. Newer techniques and speed improvements have resulted in deeper knowledge about these pathways, resulting in refined models that tend to be large and complex, making it difficult for a person to remember all aspects of it. Thus, computer models are needed to analyze them. We want to build such a system that allows modeling of biological systems and pathways in such a way that we can answer questions about them. Many existing models focus on structural and/or factoid questions, using surface-level knowledge that does not require understanding the underlying model. We believe these are not the kind of questions that a biologist may ask someone to test their understanding of the biological processes. We want our system to answer the kind of questions a biologist may ask. Such questions appear in early college level text books. Thus the main goal of our thesis is to develop a system that allows us to encode knowledge about biological pathways and answer such questions about them demonstrating understanding of the pathway. To that end, we develop a language that will allow posing such questions and illustrate the utility of our framework with various applications in the biological domain. We use some existing tools with modifications to accomplish our goal. Finally, we apply our system to real world applications by extracting pathway knowledge from text and answering questions related to drug development.Comment: thesi
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