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Computational Modeling of Signaling Networks

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Cover of 'Computational Modeling of Signaling Networks'

Table of Contents

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    Book Overview
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    Chapter 1 Design Principles Underlying Robust Adaptation of Complex Biochemical Networks
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    Chapter 2 Multi-Dimensional Analysis of Biochemical Network Dynamics Using pyDYVIPAC
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    Chapter 3 A Practical Guide for the Efficient Formulation and Calibration of Large, Energy- and Rule-Based Models of Cellular Signal Transduction
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    Chapter 4 Systems Biology: Identifiability Analysis and Parameter Identification via Systems-Biology-Informed Neural Networks
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    Chapter 5 A Practical Guide to Reproducible Modeling for Biochemical Networks
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    Chapter 6 Integrating Multi-Omics Data to Construct Reliable Interconnected Models of Signaling, Gene Regulatory, and Metabolic Pathways
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    Chapter 7 Efficient Quantification of Extrinsic Fluctuations via Stochastic Simulations
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    Chapter 8 Meta-Dynamic Network Modelling for Biochemical Networks
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    Chapter 9 Rapid Particle-Based Simulations of Cellular Signalling with the FLAME-Accelerated Signalling Tool (FaST) and GPUs
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    Chapter 10 Modeling Cellular Signaling Variability Based on Single-Cell Data: The TGFβ-SMAD Signaling Pathway
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    Chapter 11 Quantitative Imaging Analysis of NF-κB for Mathematical Modeling Applications
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    Chapter 12 Resolving Crosstalk Between Signaling Pathways Using Mathematical Modeling and Time-Resolved Single Cell Data
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    Chapter 13 Live-Cell Sender-Receiver Co-cultures for Quantitative Measurement of Paracrine Signaling Dynamics, Gene Expression, and Drug Response.
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    Chapter 14 Application of Optogenetics to Probe the Signaling Dynamics of Cell Fate Decision-Making
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    Chapter 15 Computational Random Mutagenesis to Investigate RAS Mutant Signaling
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    Chapter 16 Mathematically Modeling the Effect of Endocrine and Cdk4/6 Inhibitor Therapies on Breast Cancer Cells
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    Chapter 17 SynDISCO: A Mechanistic Modeling-Based Framework for Predictive Prioritization of Synergistic Drug Combinations Targeting Cell Signalling Networks
Attention for Chapter 13: Live-Cell Sender-Receiver Co-cultures for Quantitative Measurement of Paracrine Signaling Dynamics, Gene Expression, and Drug Response.
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Chapter title
Live-Cell Sender-Receiver Co-cultures for Quantitative Measurement of Paracrine Signaling Dynamics, Gene Expression, and Drug Response.
Chapter number 13
Book title
Computational Modeling of Signaling Networks
Published in
Methods in molecular biology, January 2023
DOI 10.1007/978-1-0716-3008-2_13
Pubmed ID
37074584
Book ISBNs
978-1-07-163007-5, 978-1-07-163008-2
Authors

Pargett, Michael, Ram, Abhineet R, Murthy, Vaibhav, Davies, Alexander E, Ram, Abhineet R., Davies, Alexander E.

Abstract

Paracrine signaling is a fundamental process regulating tissue development, repair, and pathogenesis of diseases such as cancer. Herein we describe a 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 reporters, the use of this system to ask diverse experimental questions and screen drugs blocking intracellular communication, data collection, and the use of computational approaches to model and interpret these experiments.

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Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 April 2023.
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#20,947,537
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#10,158
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Outputs of similar age from Methods in molecular biology
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