20,169 research outputs found

    Membrane Systems and Petri Net Synthesis

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    Automated synthesis from behavioural specifications is an attractive and powerful way of constructing concurrent systems. Here we focus on the problem of synthesising a membrane system from a behavioural specification given in the form of a transition system which specifies the desired state space of the system to be constructed. We demonstrate how a Petri net solution to this problem, based on the notion of region of a transition system, yields a method of automated synthesis of membrane systems from state spaces.Comment: In Proceedings MeCBIC 2012, arXiv:1211.347

    Catalytic and communicating Petri nets are Turing complete

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    In most studies about the expressiveness of Petri nets, the focus has been put either on adding suitable arcs or on assuring that a complete snapshot of the system can be obtained. While the former still complies with the intuition on Petri nets, the second is somehow an orthogonal approach, as Petri nets are distributed in nature. Here, inspired by membrane computing, we study some classes of Petri nets where the distribution is partially kept and which are still Turing complete

    Evolution and the Second Law of Thermodynamics: Effectively Communicating to Non-Technicians

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    Given the degree of disbelief in the theory of evolution by the wider public, scientists need to develop a collection of clear explanations and metaphors that demonstrate the working of the theory and the flaws in antievolutionist arguments. This paper presents tools of this sort for countering the anti-evolutionist claim that evolutionary mechanisms are inconsistent with the second law of thermodynamics. Images are provided to replace the traditional misunderstanding of the law, i.e., “everything always gets more disordered over time,” with a more clear sense of the way in which entropy tends to increase allowing a thermally isolated system access to a greater number of microstates. Accessible explanations are also provided for the ways in which individual organisms are able to minimize entropy and the advantages this conveys

    metaSHARK: software for automated metabolic network prediction from DNA sequence and its application to the genomes of Plasmodium falciparum and Eimeria tenella

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    The metabolic SearcH And Reconstruction Kit (metaSHARK) is a new fully automated software package for the detection of enzyme-encoding genes within unannotated genome data and their visualization in the context of the surrounding metabolic network. The gene detection package (SHARKhunt) runs on a Linux systemand requires only a set of raw DNA sequences (genomic, expressed sequence tag and/ or genome survey sequence) as input. Its output may be uploaded to our web-based visualization tool (SHARKview) for exploring and comparing data from different organisms. We first demonstrate the utility of the software by comparing its results for the raw Plasmodium falciparum genome with the manual annotations available at the PlasmoDB and PlasmoCyc websites. We then apply SHARKhunt to the unannotated genome sequences of the coccidian parasite Eimeria tenella and observe that, at an E-value cut-off of 10(-20), our software makes 142 additional assertions of enzymatic function compared with a recent annotation package working with translated open reading frame sequences. The ability of the software to cope with low levels of sequence coverage is investigated by analyzing assemblies of the E.tenella genome at estimated coverages from 0.5x to 7.5x. Lastly, as an example of how metaSHARK can be used to evaluate the genomic evidence for specific metabolic pathways, we present a study of coenzyme A biosynthesis in P.falciparum and E.tenella

    Abstracting Asynchronous Multi-Valued Networks: An Initial Investigation

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    Multi-valued networks provide a simple yet expressive qualitative state based modelling approach for biological systems. In this paper we develop an abstraction theory for asynchronous multi-valued network models that allows the state space of a model to be reduced while preserving key properties of the model. The abstraction theory therefore provides a mechanism for coping with the state space explosion problem and supports the analysis and comparison of multi-valued networks. We take as our starting point the abstraction theory for synchronous multi-valued networks which is based on the finite set of traces that represent the behaviour of such a model. The problem with extending this approach to the asynchronous case is that we can now have an infinite set of traces associated with a model making a simple trace inclusion test infeasible. To address this we develop a decision procedure for checking asynchronous abstractions based on using the finite state graph of an asynchronous multi-valued network to reason about its trace semantics. We illustrate the abstraction techniques developed by considering a detailed case study based on a multi-valued network model of the regulation of tryptophan biosynthesis in Escherichia coli.Comment: Presented at MeCBIC 201

    Supported liquid membranes: stabilization by gelation

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    A new method has been developed to increase the stability of supported liquid membranes. By applying a homogeneous gel network in the pores of the support both the mechanical stability (against liquid displacement) and the long term permeability increase substantially. The flux decreases only slightly because of the open structure of the gel network. A second technique, by which a thin dense gel layer is applied to the feed side of the membrane, results in a specific suppression of the formation of emulsion droplets. The stability of the membrane increases by this treatment to values which are very promising

    Computational Modeling for the Activation Cycle of G-proteins by G-protein-coupled Receptors

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    In this paper, we survey five different computational modeling methods. For comparison, we use the activation cycle of G-proteins that regulate cellular signaling events downstream of G-protein-coupled receptors (GPCRs) as a driving example. Starting from an existing Ordinary Differential Equations (ODEs) model, we implement the G-protein cycle in the stochastic Pi-calculus using SPiM, as Petri-nets using Cell Illustrator, in the Kappa Language using Cellucidate, and in Bio-PEPA using the Bio-PEPA eclipse plug in. We also provide a high-level notation to abstract away from communication primitives that may be unfamiliar to the average biologist, and we show how to translate high-level programs into stochastic Pi-calculus processes and chemical reactions.Comment: In Proceedings MeCBIC 2010, arXiv:1011.005
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