Membrane systems with promoters/inhibitors

Bottoni, Paolo; Martı́n-Vide, Carlos; Păun, Gheorghe; Rozenberg, Grzegorz

doi:10.1007/s00236-002-0090-7

Cited by 52 publications

(34 citation statements)

References 8 publications

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“…In fact, ours is strictly weaker. This is because one-membrane non-cooperative P systems with promoters are already universal [4]; however, as shown earlier, non-cooperative signaling systems are not universal. In contrast to these, signaling systems (which are not necessarily non-cooperative) are universal as well.…”

Section: Discussion and Future Workmentioning

confidence: 91%

“…Indeed, one can show that a signaling system can be directly simulated by a one-membrane P system with promoters. However, since one-membrane non-cooperative P systems with promoters are known to be universal [4], our decidability results on noncooperative signaling systems have a nice implication: our signals are strictly weaker than promoters (and hence have more decidable properties). The decidability results also imply that, as shown in the paper, non-cooperative signaling systems and vector addition systems (i.e., Petri nets) have incomparable computing power, though both models have a decidable configuration-to-configuration reachability.…”

Section: Introductionmentioning

confidence: 93%

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Signaling P Systems and Verification Problems

Dang

Ibarra

et al. 2005

Automata, Languages and Programming

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Abstract.We introduce a new model of membrane computing system (or P system), called signaling P system. It turns out that signaling systems are a form of P systems with promoters that have been studied earlier in the literature. However, unlike non-cooperative P systems with promoters, which are known to be universal, noncooperative signaling systems have decidable reachability properties. Our focus in this paper is on verification problems of signaling systems; i.e., algorithmic solutions to a verification query on whether a given signaling system satisfies some desired behavioral property. Such solutions not only help us understand the power of "maximal parallelism" in P systems but also would provide a way to validate a (signaling) P system in vitro through digital computers when the P system is intended to simulate living cells. We present decidable and undecidable properties of the model of non-cooperative signaling systems using proof techniques that we believe are new in the P system area. For the positive results, we use a form of "upper-closed sets" to serve as a symbolic representation for configuration sets of the system, and prove decidable symbolic modelchecking properties about them using backward reachability analysis. For the negative results, we use a reduction via the undecidability of Hilbert's Tenth Problem. This is in contrast to previous proofs of universality in P systems where almost always the reduction is via matrix grammar with appearance checking or through Minsky's two-counter machines. Here, we employ a new tool using Diophantine equations, which facilitates elegant proofs of the undecidable results. With multiplication being easily implemented under maximal parallelism, we feel that our new technique is of interest in its own right and might find additional applications in P systems.

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Section: Discussion and Future Workmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 93%

Signaling P Systems and Verification Problems

Dang

Ibarra

et al. 2005

Automata, Languages and Programming

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“…Promoters It is now assumed that a reaction rule can have the form lhs r → rhs r | c meaning that c is a promoter object which has to be present for the rule to be executed [6]. It should be stressed that such an object is not a catalyst since catalysts are actively involved in reactions, whereas a single occurrence of c in its role of promoter may enable simultaneously two or more executions of the rule.…”

Section: Other Extensionsmentioning

confidence: 99%

“…In this case, a reaction rule can have the form lhs r → rhs r | ¬c meaning that c is an object which, when present in the compartment, inhibits the execution of this rule [6]. Again, and for the same reason as with promoters, we need to extend PTL-nets, in this case with (weighted) inhibitor arcs, represented by arcs with small circles at the end (note that activator and inhibitor arcs are existing extensions of the standard Petri net model).…”

Section: Other Extensionsmentioning

confidence: 99%

Synchrony and Asynchrony in Membrane Systems

Kleijn

Koutny

2006

Lecture Notes in Computer Science

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Abstract. We consider synchrony and asynchrony in the behaviour of various models of membrane systems, which may differ in the way individual reactions are defined as well as in the way multisets of these reactions can be executed in a single computational step. We concentrate on the properties of ongoing computations, including the unbounded ones. Our focus is on the properties of system states involved in such computations as well as on concurrency and causality relationships between executed reactions. This should be contrasted with the approach which investigates different notions of 'results' produced through halting computations of membrane systems. As a formal behavioural model we use Petri nets and their processes which capture the notion of an execution in concurrent contexts. We continue our earlier work reported in [14], where a systematic and structural link has been established between a basic class of membrane systems and Petri nets. Here, we look at some natural extensions of this basic class of membrane systems and investigate the ways in which they can be represented within the behavioural model provided by Petri nets.

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“…In the final section several open problems are also proposed. In the following sections we suppose the reader familiar with the basic knowledge of P systems and in particular with P systems using promoters/inhibitors (for details the reader can consult [2] and [7]). …”

Section: Introductionmentioning

confidence: 99%

Computing using signals: from cells to P systems

Ardelean

Cavaliere²,

Sburlan

2004

Soft Comput

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Abstract. In cell biology one of the fundamental topic is the study of how biological signals are managed by cells. Signals can arise from inside the cell or from the external environment and the correct answer to certain signals is essential for bacteria to survive in a certain environment. Starting from these biological motivations we consider a model of P systems where the computation is controlled by signals which move across the regions. In particular, we consider Signals-Based P systems where the symbol-objects cannot be moved and the rules can be activated/inactivated using a finite number of signals (signal-promoters) moved across the membranes; differently from standard P systems using promoters, in our case promoters cannot be created during the computation. After discussing the biological motivations we show how this model becomes universal when it uses one catalyst, and a bounded number of signal-promoters.

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Membrane systems with promoters/inhibitors

Cited by 52 publications

References 8 publications

Signaling P Systems and Verification Problems

Signaling P Systems and Verification Problems

Synchrony and Asynchrony in Membrane Systems

Computing using signals: from cells to P systems

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