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Titlebook: Computational Methods in Systems Biology; 10th International C David Gilbert,Monika Heiner Conference proceedings 2012 Springer-Verlag Berl

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A Simple Model to Control Growth Rate of Synthetic E. coli during the Exponential Phase: Model Analyeover, an analytic expression of the growth rate during the exponential phase as function of the input is derived. A relevant problem is that of identifiability of the parameters of this expression supposing noisy measurements of exponential growth rate. We present such an identifiability study that we validate . with synthetic measurements.
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0302-9743 The papers cover the analysis of biological systems, networks, and data ranging from intercellular to multiscale. Topics included high-performance computing, and for the first time papers on synthetic biology.978-3-642-33635-5978-3-642-33636-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
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https://doi.org/10.1007/978-3-031-06645-0sess them with COSMOS, a statistical model checker for HASL model checking. We demonstrate that this allows assessing the “performances” of a biological system beyond the capability of other stochastic logics.
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Aaron M. Ellison,Manisha V. Patelows synchronization of a group of cells in animal development. Comparing the results of stochastic simulation with deterministic and MC approximation, we show the benefits of our approach. The reduction presented here is potentially applicable to a broad range of highly regular systems.
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Bimodal Protein Distributions in Heterogeneous Oscillating Systemshe bimodal distribution depends on the magnitude of cell-to-cell variability. We quantify this time using the Kullback-Leibler divergence. The implications of our findings for single-cell experiments are discussed.
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