Abstract

Molecular signaling networks drive a diverse range of cellular decisions, including whether to proliferate, how and when to die, and many processes in between. Such networks often connect hundreds of proteins, genes, and processes. Understanding these complex networks is aided by computational modeling, but these tools require extensive programming knowledge. In this article, we describe a user-friendly, programming-free network simulation tool called Netflux (https://github.com/saucermanlab/Netflux). Over the last decade, Netflux has been used to construct numerous predictive network models that have deepened our understanding of how complex biological networks make cell decisions. Here, we provide a Netflux tutorial that covers how to construct a network model and then simulate network responses to perturbations. Upon completion of this tutorial, you will be able to construct your own model in Netflux and simulate how perturbations to proteins and genes propagate through signaling and gene-regulatory networks.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

* Added several paragraphs of introduction and a new Figure 1.

* https://github.com/saucermanlab/Netflux

Details

Title
Logic-based modeling of biological networks with Netflux
Author
Clark, Alexander Phillip; Chowkwale, Mukti; Paap, Alexander; Dang, Stephen; Saucerman, Jeffrey J
University/institution
Cold Spring Harbor Laboratory Press
Section
Confirmatory Results
Publication year
2024
Publication date
Nov 14, 2024
Publisher
Cold Spring Harbor Laboratory Press
ISSN
2692-8205
Source type
Working Paper
Language of publication
English
ProQuest document ID
2914944596
Copyright
© 2024. This article is published under http://creativecommons.org/licenses/by/4.0/ (“the License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.