1,721,011 research outputs found

    Studying cancer-cell populations by programmable models of networks

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    We draw the basic lines for an approach to build mathematical and programmable network models, to be applied in the study of populations of cancer-cells at different stages of disease development. The methodology we propose uses a stochastic Concurrent Constraint Programming language, a flexible stochastic modelling language employed to code networks of agents. It is applied to (and partially motivated by) the study of differently characterized populations of prostate cancer cells. In particular, we prove how our method is suitable to systematically reconstruct and compare different mathematical models of prostate cancer growth—together with interactions with different kinds of hormone therapy—at different levels of refinement. Moreover, we show our technique at work in analysing the nature of noise and in the possible presence of competing mechanisms in the models proposed

    Rank-based simulation on acyclic graphs.

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    The simulation preorder is widely used both as a behavioral relation in concurrent systems, and as an abstraction tool to reduce the state space in model checking, were memory requirement is clearly a critical issue. Therefore, in this context a simulation algorithm should address both time and space efficiency. In this paper, we rely on the notion of rank to design an efficient simulation algorithm. It turns out that such algorithm outperforms-both in terms of time and in terms of space-the best simulation algorithms in the literature, on the class of acyclic graphs

    The axiom of elementary sets. I: Three-variable statements of set-pairing

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    Research report n.19/02. Dipartimento di Matematica e Informatica, Univ. di Perugia

    The axiom of elementary sets. II: The edge of Peircean expressibility

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    Research report n.20/02. Dipartimento di Matematica e Informatica, Univ. di Perugia

    Uniform relational frameworks for modal inferences

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    Proc. of CILC'04 - Italian Conference on Computational Logi

    Hybrid dynamics of stochastic programs

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    We provide Stochastic Concurrent Constraint Programming (sCCP), a stochastic process algebra based on CCP, with a semantics in terms of hybrid automata. We associate with each sCCP program both a stochastic and a non-deterministic hybrid automaton. Then, we compare such automata with the standard stochastic semantics (given by a Continuous Time Markov Chain) and the one based on ordinary differential equations, obtained by a fluid-flow approximation technique. We discuss in detail two case studies: Repressilator and the Circadian Clock, with particular regard to the robustness exhibited by the different semantic models and to the effect of discreteness in dynamical evolution of such systems
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