Clark Alexander P, Chowkwale Mukti, Paap Alexander, Dang Stephen, Saucerman Jeffrey J
Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United States of America.
Robert M. Berne Cardiovascular Research Center, University of Virginia, Charlottesville, Virginia, United States of America.
PLoS Comput Biol. 2025 Apr 4;21(4):e1012864. doi: 10.1371/journal.pcbi.1012864. eCollection 2025 Apr.
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. 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.
分子信号网络驱动着各种各样的细胞决策，包括是否增殖、如何以及何时死亡，以及其间的许多过程。此类网络通常连接着数百种蛋白质、基因和过程。计算建模有助于理解这些复杂网络，但这些工具需要广泛的编程知识。在本文中，我们描述了一种名为Netflux的用户友好型、无需编程的网络模拟工具。在过去十年中，Netflux已被用于构建众多预测性网络模型，这些模型加深了我们对复杂生物网络如何做出细胞决策的理解。在这里，我们提供一个Netflux教程，涵盖如何构建网络模型，然后模拟网络对扰动的响应。完成本教程后，你将能够在Netflux中构建自己的模型，并模拟蛋白质和基因的扰动如何通过信号传导和基因调控网络传播。
