1,720,990 research outputs found
Encoding Boolean networks into reaction systems for investigating causal dependencies in gene regulation
No full textGene regulatory networks represent the interactions among genes regulating the activation of specific cell functionalities. They have been successfully modelled using Boolean networks, where a set of Boolean variables model the activation state of each gene, and Boolean functions model positive and negative influences among genes. Moreover, when the effect of such influences is additive, threshold Boolean networks, in which Boolean functions are replaced by simpler threshold functions, turned out to be particularly effective. In this paper we propose a systematic translation of threshold Boolean networks into Ehrenfeucht and Rozenberg's reaction systems. Our translation produces a non redundant set of reactions, each using a minimal set of objects. This translation allows us to simulate the behaviour of a general threshold Boolean network by simply executing the (closed) reaction system we obtain, and to investigate causality relations among genes by applying tools available for reaction systems. We implemented our translation in an open-source tool and applied it in two case studies: the gene regulation network of segment polarity in Drosophila melanogaster and the one controlling the differentiation of Th cells in the immune system. In both case studies, we investigate causalities among genes in the reaction system obtained from the translation by applying a tool for the computation of formula based predictors. In the context of the second case study, we show that also Boolean networks with non-additive influences and modelling genes with multiple expression levels can be dealt with by our approach
Natural Computing: Foreword
No full textBuilding a bridge between computer science and natural sciences, natural computing is the field of research that investigates human-designed computing inspired by nature as well as computing taking place in nature. It investigates models and computational techniques inspired by nature, and also it investigates, in terms of information processing, phenomena taking place in natur
Timed Automata with Urgent Transitions
No full textIn this paper we propose an extension to the formalism of timed automata by allowing urgent transitions. A urgent transition is a transition which must be taken within a fixed time interval from its enabling time. We give a set of rules formally describing the behaviour of urgent transitions and we show that, from a language theoretic point of view, the addition of urgency does not improve the expressive power of timed automata. However, from a specification point of view, the use of urgent transitions is crucial, especially in modular specification of systems
Tumour suppression by Immune System through Stochastic Oscillations
No full textThe well-known Kirschner–Panetta model for tumour–immune System interplay [Kirschner, D., Panetta, J.C., 1998. Modelling immunotherapy of the tumour–immune interaction. J. Math. Biol. 37 (3), 235–252] reproduces a number of features of this essential interaction, but it excludes the possibility of tumour suppression by the immune system in the absence of therapy. Here we present a hybrid–stochastic version of that model. In this new framework, we show that in reality the model is also able to reproduce the suppression, through stochastic extinction after the first spike of an oscillation
Characterization and computation of ancestors in reaction systems
No full textIn reaction systems, preimages and nth ancestors are sets of reactants leading to the production of a target set of products in either 1 or n steps, respectively. Many computational problems on preimages and ancestors, such as finding all minimum-cardinality nth ancestors, computing their size or counting them, are intractable. In this paper, we characterize all nth ancestors using a Boolean formula that can be computed in polynomial time. Once simplified, this formula can be exploited to easily solve all preimage and ancestor problems. This allows us to directly relate the difficulty of ancestor problems to the cost of the simplification so that new insights into computational complexity investigations can be achieved. In particular, we focus on two problems: (i) deciding whether a preimage/nth ancestor exists and (ii) finding a preimage/nth ancestor of minimal size. Our approach is constructive, it aims at finding classes of reactions systems for which the ancestor problems can be solved in polynomial time, in exact or approximate way
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