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Possibilistic information theory is a flexible approach to old and new forms of coding; it is based on possibilities and patterns, rather than pointwise probabilities and traditional statistics. Here we fill up a gap of the possibilistic approach, and extend it to the case of error detection, while so far only error correction had been considered. [ABSTRACT FROM AUTHOR]

We investigate the limit behavior of a class of stochastic hybrid systems obtained by hybrid approximation of Stochastic Concurrent Constraint Programming (sCCP). We prove that a sequence of Continuous Time Markov Chain (CTMC), constructed from sCCP programs parametrically with respect to a notion of system size, converges a.s., in the limit of divergent size, to the hybrid approximation. [ABSTRACT FROM AUTHOR]

We present a technique to associate to stochastic programs written in stochastic Concurrent Constraint Programming a semantics in terms of a lattice of hybrid automata. The aim of this construction is to provide a framework to approximate the stochastic behavior by a mixed discrete/continuous dynamics with a variable degree of discreteness. [ABSTRACT FROM AUTHOR]

In this paper we focus on the relation between models of biological systems consisting of ordinary differential equations (ODE) and models written in a stochastic and concurrent paradigm (sCCP stochastic Concurrent Constraint Programming). In particular, we define a method to associate a set of ODE΄s to an sCCP program and a method converting ODE΄s into sCCP programs. Then we study the properties of these two translations. Specifically, we show that the mapping from sCCP to ODE΄s preserves rate semantics for the class of biochemical models (i.e. chemical kinetics is maintained) and we investigate the invertibility properties of the two mappings. Finally, we concentrate on the question of behavioral preservation, i.e if the models obtained applying the mappings have the same dynamics. We give a convergence theorem in the direction from ODE΄s to sCCP and we provide several well-known examples in which this property fails in the inverse direction, discussing them in detail. [ABSTRACT FROM AUTHOR]

Several process algebras for modelling hybrid systems have appeared in the literature in recent years. These all assume that continuous variables in the system are modelled monolithically, often with the differential equations embedded explicitly in the syntax of the process algebra expression. In HYPE an alternative approach is taken which offers finer-grained modelling with each flow or influence affecting a variable modelled separately. The overall behaviour then emerges as the composition of these flows. This approach is supported by an operational semantics which distinguishes states as collections of flows and which is supported by an equivalence which satisfies the property that bisimilar HYPE models give rise to the same sets of continuous behaviours. [ABSTRACT FROM AUTHOR]

Hybrid Systems are dynamical systems presenting both discrete and continuous evolution. Hybrid Automata are a formal model for hybrid systems, originally proposed to study embedded systems, where a discrete control acts on a continuously changing environment. The presence of both discrete and continuous dynamics makes this formalism appealing also for modeling biological systems. However, the situation in this case is subtler, as there is no natural separation into discrete and continuous components. No surprise, then, that hybrid automata have been used in systems biology in rather different ways. Some approaches, like the description of biological switches, concentrate on the use of model-checking routines. Other applications, like the switching between continuous and discrete/stochastic simulation, focus on the exploitation of the interplay between discreteness and continuity in order to reduce the computational burden of numerical simulation, yet maintaining an acceptable precision. We will survey the use of hybrid automata in systems biology, through a series of cases studies that we deem interesting and paradigmatic. [ABSTRACT FROM AUTHOR]

We put forward a method to map stochastic Π-calculus processes in chemical ground form into hybrid automata, a class of dynamical systems with both discrete and continuous evolution. The key ingredient is the separation of control and molecular terms, which turns out to be related to the conservation properties of the system. [ABSTRACT FROM AUTHOR]

We deal with DNA combinatorial code constructions, as found in the literature, taking the point of view of possibilistic information theory and possibilistic coding theory. The possibilistic framework allows one to tackle an intriguing informationtheoretic question: what is channel noise in molecular computation? We examine in detail two representative DNA string distances used for DNA code constructions and point out the merits of the first and the demerits of the second. The two string distances are based on the reverse Hamming distance as required to account for hybridisation of DNA strings. [ABSTRACT FROM AUTHOR]

We introduce a data structure, the Bundled Suffix Tree (BUST), that is a generalization of a Suffix Tree (ST). To build a BuST we use an alphabet Σ together with a non-transitive relation ≈ among its letters. Following the path of a substring β within a BUST, constructed over a text α of length n, not only the positions of the exact occurrences of β in α are found (as in a ST), but also the positions of all the substrings α1, α2, α3 ⋯ that are related with β via the relation ≈ among the characters of ∑, for example strings at a certain "distance" from β. A BuST contains O(n1+δ) additional nodes (δ < 1) in probability, and is constructed in O(n1+δ) steps. In the worst case it contains O(n2) nodes. [ABSTRACT FROM AUTHOR]

We present a version of the CCP paradigm, which is both distributed and probabilistic. We consider networks with a fixed number of nodes, each of them possessing a local and independent constraint store. While locally the computations evolve asynchronously, following the usual rules of (probabilistic) CCP, the communications among different nodes are synchronous. There are channels, and through them different objects can be exchanged: constraints, agents and channel themselves. In addition, all this activities are embedded in a probabilistic scheme based on a discrete model of time, both locally and globally. Finally we enhance the language with the capability of performing an automatic remote synchronization of variables belonging to different constraint stores. [ABSTRACT FROM AUTHOR]

My research interests are mainly focused on concurrent approaches to global optimization problems. Optimization tasks have two main conflicting features: they are both very difficult and central to a lot of the applications computer science faces daily. The problems I'm most interested in stem out from biology, protein folding being the principal one.Pointers to references describing the problems and the techniques mentioned here can be found in the papers cited in the reference section. They are all available on-line at http:www.dimi.uniud.it/bortolus. [ABSTRACT FROM AUTHOR]