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We describe Dizzy, a software tool for stochastically and deterministically modeling the spatially homogeneous kinetics of integrated large-scale genetic, metabolic, and signaling networks. Notable features include a modular simulation framework, reusable modeling elements, complex kinetic rate laws, multi-step reaction processes, steady-state noise(More)
  • D Orrell, L Smith, J Barkmeijer, T Palmer
  • 2001
Operational forecasting is hampered both by the rapid divergence of nearby initial conditions and by error in the underlying model. Interest in chaos has fuelled much work on the first of these two issues, this paper focuses on the second. A new approach to quantifying state-dependent model error, the local model drift, is derived and deployed both in(More)
Error in weather forecasting is due to inaccuracy both in the models used, and in the estimate of the current atmospheric state at which the model is initiated. Because weather models are thought to be chaotic, and therefore sensitive to initial condition, the technique of ensemble forecasting has been developed in part to address the latter effect. An(More)
Nonlinear dynamical models are frequently used to approximate and predict observed physical, biological, and economic systems. Such models will be subject to errors both in the model dynamics, and the observations of the underlying system. In order to improve models, it is necessary to understand the causes of error growth. A complication with chaotic(More)
Positive and negative feedback loops, for example, where a protein regulates its own transcription, play an important role in many genetic regulatory networks. Such systems will be subject to internal noise, which occurs due to the small number of molecules taking part in some reactions. This paper examines the effect of feedback loops on noise levels.(More)
Bifurcation diagrams which allow one to visualise changes in the behaviour of low dimensional nonlinear maps as a parameter is altered are common. Visualisation in higher dimensional systems is more difficult. A straightforward method to visualise bifurcations in flows of high dimensional nonlinear dynamical systems is presented, using the Lorenz '96(More)
Transcriptional noise is known to play a crucial role in heterogeneity in bacteria and yeast. Mammalian macrophages are known to exhibit cell-to-cell variation in their responses to pathogens, but the source of this heterogeneity is not known. We have developed a detailed stochastic model of gene expression that takes into account scaling effects due to(More)
Genetic networks are often affected by stochastic noise, due to the low number of molecules taking part in certain reactions. In complex regulatory networks, noise in any one chemical species may induce noise in the rest of the system. In this paper, we analyse the sources of stochastic noise in the yeast galactose utilization pathway at the level of the(More)