| Autor: |
Clark AP; Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America., Chowkwale M; Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America., Paap A; Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America., Dang S; Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America., Saucerman JJ; Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States of America.; Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, VA, United States of America. |
| Abstrakt: |
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. |
