no / This chapter gives an overview of an integrated software suite, the Infobiotics Workbench, which is based on a novel spatial discrete-stochastic P systems modelling framework. The Workbench incorporates three important features, simu- lation, model checking and optimisation. Its capability for building, analysing and optimising large spatially discrete and stochastic models of multicellular systems makes it a useful, coherent and comprehensive in silico tool in systems and synthetic biology research. / EPSRC / The full text is unavailable due to publisher copyright restrictions on book chapters.

Yes / Structural and behavioural properties of models are very important in development of complex systems and applications. In this paper, we investigate such properties for some classes of SN P systems. First, a class of SN P systems associated to a set of routing problems are investigated through their matrix representation. This allows to make certain connections amongst some of these problems. Secondly, the behavioural properties of these SN P systems are formally verified through a natural and direct mapping of these models into kP systems which are equipped with adequate formal verification methods and tools. Some examples are used to prove the effectiveness of the verification approach. / EPSRC research grant EP/R043787/1; DOST-ERDT research grants; Semirara Mining Corp; UPD-OVCRD;

Yes / Computational models are perceived as an attractive alternative to mathematical models (e.g., ordinary differential equations). These models incorporate a set of methods for specifying, modeling, testing, and simulating biological systems. In addition, they can be analyzed using algorithmic techniques (e.g., formal verification). This paper shows how formal verification is utilized in systems and synthetic biology through qualitative vs quantitative analysis. Here, we choose two well-known case studies: quorum sensing in P. aeruginosas and pulse generator. The paper reports verification analysis of two systems carried out using some model checking tools, integrated to the Infobiotics Workbench platform, where system models are based on stochastic P systems. / EPSRC

DNA-basierte Systeme beschreiben formal ein alternatives Berechnungskonzept, beruhend auf der Anwendung molekularbiologischer Operationen. Der Grundgedanke ist dabei die Entwicklung alternativer und universeller Rechnerarchitekturen. Infolge der zugrunde liegenden maximalen Parallelität sowie der hohen Komplexität entsprechender Systeme ist die Korrektheit jedoch schwer zu beweisen. Um dies zu ermöglichen werden in der Arbeit zunächst für drei verschiedene Systemklassen mit unterschiedlichen Berechnungsparadigmen strukturelle operationelle Semantiken definiert und bekannte Formalismen der Prozesstheorie adaptiert. Nachfolgend werden Tableaubeweissysteme beschrieben, mithilfe derer einerseits Invarianten und andererseits die jeweilige Korrektheit von DNA-basierten Systemen mit universeller Berechnungsstärke bewiesen werden können. Durch Anwendung dieser Konzepte konnte für drei universelle Systeme die Korrektheit gezeigt und für ein System widerlegt werden.

DNA-basierte Systeme beschreiben formal ein alternatives Berechnungskonzept, beruhend auf der Anwendung molekularbiologischer Operationen. Der Grundgedanke ist dabei die Entwicklung alternativer und universeller Rechnerarchitekturen. Infolge der zugrunde liegenden maximalen Parallelität sowie der hohen Komplexität entsprechender Systeme ist die Korrektheit jedoch schwer zu beweisen. Um dies zu ermöglichen werden in der Arbeit zunächst für drei verschiedene Systemklassen mit unterschiedlichen Berechnungsparadigmen strukturelle operationelle Semantiken definiert und bekannte Formalismen der Prozesstheorie adaptiert. Nachfolgend werden Tableaubeweissysteme beschrieben, mithilfe derer einerseits Invarianten und andererseits die jeweilige Korrektheit von DNA-basierten Systemen mit universeller Berechnungsstärke bewiesen werden können. Durch Anwendung dieser Konzepte konnte für drei universelle Systeme die Korrektheit gezeigt und für ein System widerlegt werden.

No / This paper proposes an approximate optimization approach, called QEAM, which combines a P system with active membranes and a quantum-inspired evolutionary algorithm. QEAM uses the hierarchical arrangement of the compartments and developmental rules of a P system with active membranes, and the objects consisting of quantum-inspired bit individuals, a probabilistic observation and the evolutionary rules designed with quantum-inspired gates to specify the membrane algorithms. A large number of experiments carried out on benchmark instances of satisfiability problem show that QEAM outperforms QEPS (quantum-inspired evolutionary algorithm based on P systems) and its counterpart quantum-inspired evolutionary algorithm.

No / A membrane-inspired evolutionary algorithm (MIEA) is a successful instance of a model linking membrane computing and evolutionary algorithms. This paper proposes the analysis of dynamic behaviors of MIEAs by introducing a set of population diversity and convergence measures. This is the first attempt to obtain additional insights into the search capabilities of MIEAs. The analysis is performed on the MIEA, QEPS (a quantum-inspired evolutionary algorithm based on membrane computing), and its counterpart algorithm, QIEA (a quantum-inspired evolutionary algorithm), using a comparative approach in an experimental context to better understand their characteristics and performances. Also the relationship between these measures and fitness is analyzed by presenting a tendency correlation coefficient to evaluate the importance of various population and convergence measures, which is beneficial to further improvements of MIEAs. Results show that QEPS can achieve better balance between convergence and diversity than QIEA, which indicates QEPS has a stronger capacity of balancing exploration and exploitation than QIEA in order to prevent premature convergence that might occur. Experiments utilizing knapsack problems support the above made statement.

Membrane computing investigates models of computation inspired by certain features of biological cells, especially features arising because of the presence of membranes. Because of their inherent large-scale parallelism, membrane computing models (called P systems) can be fully exploited only through the use of a parallel computing platform. However, it is an open question whether it is feasible to develop an efficient and useful parallel computing platform for membrane computing applications. Such a computing platform would significantly outperform equivalent sequential computing platforms while still achieving acceptable scalability, flexibility and extensibility. To move closer to an answer to this question, I have investigated a novel approach to the development of a parallel computing platform for membrane computing applications that has the potential to deliver a good balance between performance, flexibility, scalability and extensibility. This approach involves the use of reconfigurable hardware and an intelligent software component that is able to configure the hardware to suit the specific properties of the P system to be executed. As part of my investigations, I have created a prototype computing platform called Reconfig-P based on the proposed development approach. Reconfig-P is the only existing computing platform for membrane computing applications able to support both system-level and region-level parallelism. Using an intelligent hardware source code generator called P Builder, Reconfig-P is able to realise an input P system as a hardware circuit in various ways, depending on which aspects of P systems the user wishes to emphasise at the implementation level. For example, Reconfig-P can realise a P system in a rule-oriented manner or in a region-oriented manner. P Builder provides a unified implementation framework within which the various implementation strategies can be supported. The basic principles of this framework conform to a novel design pattern called Content-Form-Strategy. The framework seamlessly integrates the currently supported implementation approaches, and facilitates the inclusion of additional implementation strategies and additional P system features. Theoretical and empirical results regarding the execution time performance and hardware resource consumption of Reconfig-P suggest that the proposed development approach is a viable means of attaining a good balance between performance, scalability, flexibility and extensibility. Most of the existing computing platforms for membrane computing applications fail to support nondeterministic object distribution, a key aspect of P systems that presents several interesting implementation challenges. I have devised an efficient algorithm for nondeterministic object distribution that is suitable for implementation in hardware. Experimental results suggest that this algorithm could be incorporated into Reconfig-P without too significantly reducing its performance or efficiency. / Thesis (PhDInformationTechnology)--University of South Australia, 2010

yes / This Workshop on Membrane Computing, at the Conference of Unconventional Computation and Natural Computation (UCNC), 12th July 2016, Manchester, UK, is the second event of this type after the Workshop at UCNC 2015 in Auckland, New Zealand*. Following the tradition of the 2015 Workshop the Proceedings are published as technical report. The Workshop consisted of one invited talk and six contributed presentations (three full papers and three extended abstracts) covering a broad spectrum of topics in Membrane Computing, from computational and complexity theory to formal verification, simulation and applications in robotics. All these papers – see below, but the last extended abstract, are included in this volume. The invited talk given by Rudolf Freund, “P SystemsWorking in Set Modes”, presented a general overview on basic topics in the theory of Membrane Computing as well as new developments and future research directions in this area. Radu Nicolescu in “Distributed and Parallel Dynamic Programming Algorithms Modelled on cP Systems” presented an interesting dynamic programming algorithm in a distributed and parallel setting based on P systems enriched with adequate data structure and programming concepts representation. Omar Belingheri, Antonio E. Porreca and Claudio Zandron showed in “P Systems with Hybrid Sets” that P systems with negative multiplicities of objects are less powerful than Turing machines. Artiom Alhazov, Rudolf Freund and Sergiu Ivanov presented in “Extended Spiking Neural P Systems with States” new results regading the newly introduced topic of spiking neural P systems where states are considered. “Selection Criteria for Statistical Model Checker”, by Mehmet E. Bakir and Mike Stannett, presented some early experiments in selecting adequate statistical model checkers for biological systems modelled with P systems. In “Towards Agent-Based Simulation of Kernel P Systems using FLAME and FLAME GPU”, Raluca Lefticaru, Luis F. Macías-Ramos, Ionuţ M. Niculescu, Laurenţiu Mierlă presented some of the advatages of implementing kernel P systems simulations in FLAME. Andrei G. Florea and Cătălin Buiu, in “An Efficient Implementation and Integration of a P Colony Simulator for Swarm Robotics Applications" presented an interesting and efficient implementation based on P colonies for swarms of Kilobot robots. *http://ucnc15.wordpress.fos.auckland.ac.nz/workshop-on-membrane-computingwmc- at-the-conference-on-unconventional-computation-natural-computation/