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

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书目名称Computational Methods in Systems Biology影响因子(影响力)




书目名称Computational Methods in Systems Biology影响因子(影响力)学科排名




书目名称Computational Methods in Systems Biology网络公开度




书目名称Computational Methods in Systems Biology网络公开度学科排名




书目名称Computational Methods in Systems Biology被引频次




书目名称Computational Methods in Systems Biology被引频次学科排名




书目名称Computational Methods in Systems Biology年度引用




书目名称Computational Methods in Systems Biology年度引用学科排名




书目名称Computational Methods in Systems Biology读者反馈




书目名称Computational Methods in Systems Biology读者反馈学科排名

Ordnance

Watemelon

Doing Research with Undergraduatesn be quantified using non-invasive imaging methods, histology is still the modality that provides the best combination of resolution and identification of cellular/sub-cellular substrate identities. The main limitation of histology is that it does not provide inherently consistent three-dimensional

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MIRE

https://doi.org/10.1007/978-3-031-06645-0sses, namely Discrete Event Stochastic Processes (DESPs). Here we demonstrate the potential of HASL based verification in the context of genetic circuits. To this aim we consider the analysis of a model of gene expression with delayed stochastic dynamics, a class of systems whose dynamics includes b

fibroblast

Aaron M. Ellison,Manisha V. Patelctable. Deterministic methods, while computationally more efficient, may fail to contribute reliable approximations for those models. In this paper, we suggest a reduction for models of cell-to-cell communication, based on symmetries of the underlying reaction network. To carry out a stochastic anal

fibroblast

Aaron M. Ellison,Manisha V. Patels to understand the underlying mechanism of interaction. In this study we explore the disjoint and overlapping community structure of an integrated network for a major fungal pathogen of many cereal crops, .. The network was generated by combining sequence, protein interaction and co-expression data

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conservative

https://doi.org/10.1007/978-3-031-06641-2 of the growth rate of the cells during the exponential phase. This model is a piecewise non-linear system with two variables (the concentrations of two gene products) and an input (an inducer). We study the qualitative dynamics of the model and the bifurcation diagram with respect to the input. Mor

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Aaron M. Ellison,Manisha V. Patelh the optimal genetic manipulations, in terms of knockout, which also guarantee the growth of the organism. We introduce a multi-objective optimisation algorithm, called Genetic Design through Multi-Objective (GDMO), and test it in several organisms to maximise the production of key intermediate met