Adams
发表于 2025-3-21 19:08:39
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Ordnance
发表于 2025-3-21 22:48:30
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Watemelon
发表于 2025-3-22 00:51:10
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
Forage饲料
发表于 2025-3-22 04:57:28
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MIRE
发表于 2025-3-22 10:45:20
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
发表于 2025-3-22 16:18:53
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
发表于 2025-3-22 21:03:25
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
贝雷帽
发表于 2025-3-22 21:43:47
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conservative
发表于 2025-3-23 04:48:32
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
河潭
发表于 2025-3-23 08:07:03
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