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Princeton University Library Catalog
Computational modeling of signaling networks / edited by Lan K. Nguyen.
New York, NY : Humana Press, 
xi, 386 pages : illustrations (chiefly color) ; 26 cm.
Cellular signal transduction
Nguyen, Lan K.
Methods in molecular biology (Clifton, N.J.) ; v. 2634.
[More in this series]
Springer protocols (Series)
[More in this series]
Methods in molecular biology, 1064-3745 ; 2634
This volume focuses on the computational modeling of cell signaling networks and the application of these models and model-based analysis to systems and personalized medicine. Chapters guide readers through various modeling approaches for signaling networks, new methods and techniques that facilitate model development and analysis, and new applications of signaling network modeling towards systems and personalized treatment of cancer. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and methods, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Computational Modeling of Signaling Networks aims to benefit a wide spectrum of readers including researchers from the biological as well as computational systems biology communities.
Includes bibliographical references and index.
Rights and reproductions note
Current copyright fee: GBP19.00 42\0.
Design Principles Underlying Robust Adaptation of Complex Biochemical Networks
High-dimensional Dynamic Analysis of Biochemical Network Dynamics using pyDYVIPAC
A Practical Guide for the Efficient Formulation and Calibration of Large, Energy Rule-Based Models of Cellular Signal Transduction
Systems Biology: Identifiability analysis and parameter identification via systems-biology informed neural networks
A Practical Guide to Reproducible Modeling for Biochemical Networks
Integrating Multi-omics Data to Construct Reliable Interconnected Models of Signaling, Gene Regulatory and Metabolic Pathways
Efficient Quantification of Extrinsic Fluctuations via Stochastic Simulations
Meta-Dynamic Network Modelling for Biochemical Networks
Rapid Particle-based Cell Signalling Simulations with the FLAME-accelerated Signalling Tool (FaST) and GPUs
Modelling Cellular Signalling Variability Based on Single-cell Data: the TGF[beta]-SMAD Signaling Pathway
Quantitative Imaging Analysis of NF-kB for Mathematical Modelling Applications
Resolving Crosstalk between Signaling Pathways using Mathematical Modeling and Time-resolved Single-cell Data
Live-cell Sender-Receiver Co-cultures for Quantitative Measurement of Paracrine Signaling Dynamics, Gene Expression, and Drug Response
Application of Optogenetics to Probe the Signaling Dynamics of Cell Fate Decision Making
Computational Random Mutagenesis to Investigate RAS Mutant Signaling
Mathematically Modeling the Effect of Endocrine and CDK4/6 Inhibitor Therapies on Breast Cancer Cells
SynDISCO: a mechanistic modelling-based framework for predictive prioritisation of synergistic drug combinations directed at cell signalling networks.
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Computational Modeling of Signaling Networks