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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Efficient Quantification of Extrinsic Fluctuations via Stochastic Simulationsen 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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Rapid Particle-Based Simulations of Cellular Signalling with the FLAME-Accelerated Signalling Tool (ls 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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Live-Cell Sender-Receiver Co-cultures for Quantitative Measurement of Paracrine Signaling Dynamics, method 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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Computational Random Mutagenesis to Investigate RAS Mutant Signalingl 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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