Metabolic Systemic Computing: Exploiting Innate Immunity within an Artificial Organism for On-line Self-Organisation and Anomaly Detection

Martelot, Erwan Le; Bentley, Peter J.

doi:10.1007/s10852-009-9103-7

Cited by 3 publications

(5 citation statements)

References 9 publications

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“…Systemic computation is a new bio-inspired model of computation that has shown considerable success for biological modeling and bio-inspired computation [6][7][8][9][10][11][12][13][14]. However until now it has only been available as a serial simulation running on conventional processors.…”

Section: Resultsmentioning

confidence: 99%

“…The simulation was implemented in ANSI C on a PowerBook Macintosh G4, enabling systemic computation programs to be simulated using conventional computer processors. Later work by Le Martelot created a second implementation on PCs with a higher-level language and visualization tools [2,[6][7][8][9][10][11][12]14]. Other work provided a discussion on the use of sensor networks to implement a systemic computer [13].…”

Section: Systemic Computationmentioning

confidence: 99%

“…To date, two simulations of this architecture have been developed, with corresponding machine and programming languages, compilers and graphical visualiser [1,6]. Extensive work has shown how this form of computer enables useful biological modeling and bio-inspired algorithms to be implemented with ease [7][8][9][10][11] and how it enables properties such as fault-tolerance and self-repairing code [12]. Research is ongoing in the improvement of the PC-based simulator, refining the systemic computation language and visualiser [10,14].…”

Section: Introductionmentioning

confidence: 99%

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Systemic Computation Using Graphics Processors

Rouhipour

Bentley

Shayani

2010

Evolvable Systems: From Biology to Hardware

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Abstract. Previous work created the systemic computer -a model of computation designed to exploit many natural properties observed in biological systems, including parallelism. The approach has been proven through two existing implementations and many biological models and visualizations. However to date the systemic computer implementations have all been sequential simulations that do not exploit the true potential of the model. In this paper the first parallel implementation of systemic computation is introduced. The GPU Systemic Computation Architecture is the first implementation that enables parallel systemic computation by exploiting multiple cores available in graphics processors. Comparisons with the serial implementation when running a genetic algorithm at different scales show that as the number of systems increases, the parallel architecture is several hundred times faster than the existing implementations, making it feasible to investigate systemic models of more complex biological systems.

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Section: Resultsmentioning

confidence: 99%

Section: Systemic Computationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Systemic Computation Using Graphics Processors

Rouhipour

Bentley

Shayani

2010

Evolvable Systems: From Biology to Hardware

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“…SC has been used to model genetic algorithms, neural networks, artificial immune systems and has demonstrated properties of flexibility, fault tolerance, self-repair and selforganisation. [29][30][31][32] The next section explains how SC can be visualised dynamically to represent and follow the flow of information in SC models. This is then followed by a study of two biological networks.…”

Section: Definitionmentioning

confidence: 99%

“…Previous work introduced a computer platform for SC 29 and explored various bio-inspired models implemented using SC and their respective properties. 28,[30][31][32] Systemic computing visualisation exploits some of the aforementioned ideas and aims at providing a unified dynamic representation of interactions and structural changes for natural and complex processes. This article follows the introduction of SC visualisation in Le Martelot and Bentley 33 and presents in detail three visualisation methods for SC using two models of biological systems.…”

Section: Introductionmentioning

confidence: 99%

Novel Visualisation and Analysis of Natural and Complex Systems Using Systemic Computation

Martelot

Bentley

2010

Information Visualization

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The study, analysis and understanding of natural processes are difficult tasks considering the complex nature of such processes. In this respect, the visual analysis of such systems can be of great help in the understanding of their behaviour. The increasing power of modern computers enables novel possible uses of computer graphics for such tasks. Previous work introduced systemic computation, a new model of computation and corresponding computer architecture aiming at enabling a clear formalism of natural and complex systems and providing tools for their analysis. Here, we present an online visualisation of dynamic systems based on this novel paradigm. The observation is done at a high level of abstraction, focussing on information flow, interactions and emergent behaviour, and enabling the identification of similarities and differences between models of complex systems. This visualisation framework is then applied to two biological networks: a bistable gene network and a MAPK signalling cascade.

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