Titlebook: Computational Modeling of Signaling Networks; Lan K. Nguyen Book 2023 Springer Science+Business Media, LLC, part of Springer Nature 2023 C

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,Fünfzehnerspiel und Zauberwürfel,en these fluctuations dictate the outcome of a cell-fate decision-making event. Thus, having an accurate estimate of these fluctuations for any biological network is extremely important. There are well-established theoretical and numerical methods to quantify the intrinsic fluctuation present within

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Raten, Beweisen, Wundern und Zaubern,ables, however, are rarely static and immutable entities, especially in a biological context. This observation undermines the predictions made by ODE models that rely on specific parameter and state variable values and limits the contexts in which their predictions remain accurate and useful. Meta-d

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https://doi.org/10.1007/978-3-319-74648-7ls in its ability to model complex features of cellular signalling pathways including stochasticity, spatial effects, and heterogeneity, thus improving our understanding of critical decision processes in biology. Yet, particle-based modelling is computationally prohibitive to implement. We recently

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The ,-Dimensional Dyadic Derivative, molecular mechanisms. Over the past decade, mathematical models have been developed based on quantitative observations, such as live-cell imaging and biochemical assays. However, it is difficult to directly integrate next-generation sequencing (NGS) data. Although highly dimensional, NGS data mostl

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https://doi.org/10.1007/978-3-319-54621-6mprehensive understanding of cellular responses, identifying points of interaction between the underlying molecular networks is essential. Here, we present an approach that allows the systematic prediction of such interactions by perturbing one pathway and quantifying the concomitant alterations in

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Sourav S. Bhowmick,Boon-Siew Seahmethod for quantitatively measuring paracrine signaling dynamics, and resultant gene expression changes, in living cells using genetically encoded signaling reporters and fluorescently tagged gene loci. We discuss considerations for selecting paracrine “sender-receiver” cell pairs, appropriate repor

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https://doi.org/10.1007/978-3-642-72025-3 programing. Here I present a protocol for decoding cell fates through systematic interrogation with optogenetics and visualization of signaling with live biosensors. Specifically, this is written for Erk control of cell fates using the optoSOS system in mammalian cells or . embryos, though it is in

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J. A. Kengmogne Tchakam,H. -G. Reimerdesl model of the RAS signaling network that has previously been developed and applied to specific RAS mutants will be adapted for the process of computational random mutagenesis. By using this model to computationally investigate the range of RAS signaling outputs that would be anticipated over a wide

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