P Systems for Biological Dynamics

Bianco, Luca; Fontana, Federico; Franco, Giuditta; Manca, Vincenzo

doi:10.1007/3-540-29937-8_3

Cited by 28 publications

(33 citation statements)

References 18 publications

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“…Although they were originally introduced as computational models, their biologically inspired structure and functioning, together with their feasibility as models of cellular and biomolecular processes, turned out to be a widely applicable modeling technique in several domains, including medicine (for immunological processes [6], and cellular tissue healing [5]), economics [16], linguistics and computer science (computer graphics, cryptography, approximate solutions to optimization problems) [4], and, of course, biology (for mechanosensitive channels [1], respiration in bacteria, photosynthesis, the protein kinase C activation [3]). …”

Section: Introductionmentioning

confidence: 99%

“…This new strategy of rule application was inspired by real 'metabolic reactions', and it seems to lead multiset based computing towards interesting simulations of biological processes, such as complex oscillations [11], the mitotic cycle [3] and the non-photochemical quenching phenomenon [12]. Overall, a new way to observe the evolution rules of a system reproducing a metabolic reaction was proposed.…”

Section: Introductionmentioning

confidence: 99%

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Regulation and Covering Problems in MP Systems

2010

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Summary. The study of efficient methods to deduce fluxes of biological reactions, by starting from experimental data, is necessary to understand the dynamics of a metabolic model, but it is also a central issue in systems biology. In this paper we report some partial results and related open problems regarding the efficient computation of regulation fluxes in metabolic P systems. By means of Log-gain theory the system dynamics can be linearized, in such a way to be described by a recurrence equations system, of which we point out a few algebraic properties, involving covering problems.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Regulation and Covering Problems in MP Systems

2010

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“…Among these models, the Metabolic P systems [11,12], shortly MP systems, proved to be relevant in the analysis of dynamics of biochemical processes, that is, structures where matter of different type is transformed by reactions. By means of MP systems models of several interesting phenomena were provided, among which we mention: the Lotka-Volterra dynamics [2,3,15], a Susceptible-Infected-Recovered epidemic [2], the Leukocyte Selective Recruitment in the immune response [2], the Protein Kinase C Activation [3], the Mitotic Cycle [14], the Pseudomonas Quorum Sensing [4] and the Non-Photochemical Quenching phenomenon [16].…”

Section: Introductionmentioning

confidence: 99%

An Algorithm for Initial Fluxes of Metabolic P Systems

Pagliarini

Franco

Manca

2009

INT J COMPUT COMMUN

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A central issue in systems biology is the study of efficient methods inferring fluxes of biological reactions by starting from experimental data. Among the different techniques proposed in the last years, the theory of Metabolic P systems, which is based on the Log-Gain principle, proved to be helpful for deducing biological fluxes from temporal series of observed dynamics. According to this approach, the algebraic systems provided by the Log-Gain principle determine the reaction fluxes underlying a system dynamics when initial fluxes are known. Here we propose a heuristic algorithm for estimating the initial fluxes, that is tested in two case studies.

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“…See [24] for a discussion of these features. P system models have been applied in a variety of domains, including algorithm solving and analysis [1,19,20,23], linguistics [6] and biology [2,8,10,11,12,22,29]. Most existing applications of membrane computing are targeted at the modelling and simulation of biological systems.…”

Section: Membrane Computing and Its Applicationsmentioning

confidence: 99%

Balancing Performance, Flexibility, and Scalability in a Parallel Computing Platform for Membrane Computing Applications

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Summary. Membrane computing investigates models of computation inspired by certain features of biological cells. To exploit the performance advantage of the large-scale parallelism of membrane computing models, it is necessary to execute them on a parallel computing platform. However, it is an open question whether it is feasible to develop a parallel computing platform for membrane computing applications that significantly outperforms equivalent sequential computing platforms while still achieving acceptable flexibility and scalability. To move closer to an answer to this question, we 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 and scalability. 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 membrane computing model to be executed. We have developed a prototype computing platform called Reconfig-P based on the approach. Reconfig-P is the first computing platform of its type to implement parallelism at both the system and region levels. In this paper, we describe Reconfig-P and evaluate its performance, flexibility and scalability. Theoretical and empirical results suggest that the implementation approach on which Reconfig-P is based is a viable means of attaining a good balance between performance, flexibility and scalability in a parallel computing platform for membrane computing applications.

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P Systems for Biological Dynamics

Cited by 28 publications

References 18 publications

Regulation and Covering Problems in MP Systems

Regulation and Covering Problems in MP Systems

An Algorithm for Initial Fluxes of Metabolic P Systems

Balancing Performance, Flexibility, and Scalability in a Parallel Computing Platform for Membrane Computing Applications

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