Titlebook: Computational Methods in Systems Biology; International Confer Muffy Calder,Stephen Gilmore Conference proceedings 2007 Springer-Verlag Ber

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Reconstruction of Mammalian Cell Cycle Regulatory Network from Microarray Data Using Stochastic Logependencies from realistic data, our method gives consistently better results than Dynamic Bayesian Networks in terms of the number of correctly reconstructed edges, sensitivity and statistical significance.

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Expressive Models for Synaptic Plasticity,learning. The two aims of our work, i.e. addressing neural mechanisms and validating and possibly improving, process calculi based modeling techniques are discussed throughout the paper, together with the results of experiments.

行為

A Unifying Framework for Modelling and Analysing Biochemical Pathways Using Petri Nets,a precise definition of biochemically interpreted stochastic Petri nets. Although our framework is based on Petri nets, it can be applied more widely to other formalisms which are used to model and analyse biochemical networks.

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tenosynovitis

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Justin Mathena,Aaron Yetter,Hoss Hostetlerare first and second moments in the two stochastic settings. To analyse the Chemical Master Equation we use some recent work of Gadgil, Lee and Othmer, and to analyse the Chemical Langevin Equation we use Ito’s Lemma. We find that there is a perfect match—both modelling regimes give the same means,

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SLUMP

Opportunities to Expand the Value of CRMboth the modelling and simulation framework of our study. We discuss the validation of the model against the available experimental data and we show some preliminary results obtained from the study of our model. All the analyses are based on stochastic simulation.