Wyniki wyszukiwania - BazTech

Ograniczanie wyników

2 Fundamenta Informaticae

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Sortuj według:

Ogranicz wyniki do:

Specialized Predictor for Reaction Systems with Context Properties

Barbuti R., Gori R., Levi F., Milazzo P.

Fundamenta Informaticae

2016

Vol. 147, nr 2/3

173--191

Reaction systems are a qualitative formalism for modeling systems of biochemical reactions characterized by the non-permanency of the elements: molecules disappear if not produced by any enabled reaction. Reaction systems execute in an environment that provides new molecules at each step. Brijder, Ehrenfeucht and Rozemberg introduced the idea of predictors. A predictor of a molecule s, for a given n, is the set of molecules to be observed in the environment to determine whether s is produced or not at step n by the system. We introduced the notion of formula based predictor, that is a propositional logic formula that precisely characterizes environments that lead to the production of s after n steps. In this paper we revise the notion of formula based predictor by defining a specialized version that assumes the environment to provide molecules according to what expressed by a temporal logic formula. As an application, we use specialized formula based predictors to give theoretical grounds to previously obtained results on a model of gene regulation.

Maximally Parallel Probabilistic Semantics for Multiset Rewriting

Barbuti R., Levi F., Milazzo P., Scatena G.

Fundamenta Informaticae

2011

Vol. 112, nr 1

1-17

Maximally parallel semantics have been proposed for many formalisms as an alternative to the standard interleaving semantics for some modelling scenarios. Nevertheless, in the probabilistic setting an affirmed interpretation of maximal parallelism still lacks. We define a synchronous maximally parallel probabilistic semantics for multiset rewriting tailored to describe, simulate and verify biological systems evolving with maximally parallel steps. Each step of the proposed semantics is parallel as each reaction can happen multiple times, and it is maximal as it leaves no enabled reaction i.e. as many reactions as possible are executed. We define a maximally parallel probabilistic semantics in terms of Discrete Time Markov Chain for systems described by stochastic multiset rewriting. We propose a simple, maximally parallel, model of Caenorhabditis elegans vulval development on which we show probabilistic simulations results.