Titlebook: Membrane Computing; 17th International C Alberto Leporati,Grzegorz Rozenberg,Claudio Zandro Conference proceedings 2017 Springer Internatio

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Applications of P Systems in Population Biology and Ecology: The Cases of MPP and APP Systemsd the Attributed Probabilistic P systems (APP systems). We describe also two case studies in which the two formalisms have been applied to the study of real ecological systems. The first case study deals with the causes of the stability of European hybrid populations of water frogs. The second case

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Simulating R Systems by P Systemsimatter annihilation rules, with a slowdown by a constant factor only. The descriptional complexity of the simulating P systems is also linear with respect to that of the simulated R system. All constants depend on how general the model of R systems is, as well as on the chosen control ingredients o

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Purely Catalytic P Systems over Integers and Their Generative Powerese systems apply catalytic rules in the maximally parallel way, even consuming absent non-catalysts, thus effectively generating vectors of arbitrary (not just non-negative) integers. The rules may only be made inapplicable by dissolution rules. However, this releases the catalysts into the immedia

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Chemical Term Reduction with Active P Systemsre simulated by the computation of the corresponding membrane system. Finding such translations could help to reason about properties of membrane computations and properties of the reduction sequences of chemical calculi in terms of each other. By translating chemical computing formalisms to membran

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P Colonies with Evolving Environmentat can only consume objects, and P colonies with one object inside each agent which uses rewriting and communication rules. We show that the first kind of P colonies with one consumer agent can generate all sets of natural numbers computed by partially blind register machines. The second kind of P c

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Solution to Motif Finding Problem in Membraneses, or motifs, in a DNA sequence. However, finding these motifs is difficult and is shown to be NP-complete. In this paper, we use a variant of P systems called Evolution-Communication P systems with Energy using string objects to solve the Motif Finding Problem in .(.)-time where . is the length of