Home
This Title All WIREs
WIREs RSS Feed
How to cite this WIREs title:
WIREs Syst Biol Med
Impact Factor: 3.542

Computational modeling of mammalian signaling networks

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract One of the most exciting developments in signal transduction research has been the proliferation of studies in which a biological discovery was initiated by computational modeling. In this study, we review the major efforts that enable such studies. First, we describe the experimental technologies that are generally used to identify the molecular components and interactions in, and dynamic behavior exhibited by, a network of interest. Next, we review the mathematical approaches that are used to model signaling network behavior. Finally, we focus on three specific instances of ‘model‐driven discovery’: cases in which computational modeling of a signaling network has led to new insights that have been verified experimentally. Copyright © 2009 John Wiley & Sons, Inc. This article is categorized under: Models of Systems Properties and Processes > Cellular Models

This WIREs title offers downloadable PowerPoint presentations of figures for non-profit, educational use, provided the content is not modified and full credit is given to the author and publication.

Download a PowerPoint presentation of all images


Mathematical approaches to model a signaling network. (a) A hypothetical signaling network that transfers information from cytosolic enzymes to transcription factors to regulate gene expression. (b) The ordinary differential equation represents the phosphorylation and dephosphorylation of the Y protein. The partial differential equation models the effects of molecular diffusion and biochemical reactions with spatial dependence. (c) Measurements of the signaling network and phenotypic output (possibly measured through flow cytometry) are analyzed together to form a reduced space partial least squares regression model. (d) Network‐based approaches. Network component analysis determines the linear weight of transcription factors on gene regulation. Extreme pathway analysis gives the minimal set of pathways that characterize the functional signaling in a network.

[ Normal View | Magnified View ]

The order (number of independent variables) of differential equation‐based models of mammalian signal transduction, plotted by publication year. In cases where one model's publication led to the creation of several derivative models, only the first model is included.

[ Normal View | Magnified View ]

Related Articles

Algorithmic and analytical methods in network biology
Multiscale modeling for biologists
Agent‐based models in translational systems biology
Integrative Bioinformatics

Browse by Topic

Models of Systems Properties and Processes > Cellular Models

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts