Department of Physics, The Pennsylvania State University, University Park, PA 16802, USA.
Phys Biol. 2012 Oct;9(5):055001. doi: 10.1088/1478-3975/9/5/055001. Epub 2012 Sep 25.
Mathematical modeling of biological processes provides deep insights into complex cellular systems. While quantitative and continuous models such as differential equations have been widely used, their use is obstructed in systems wherein the knowledge of mechanistic details and kinetic parameters is scarce. On the other hand, a wealth of molecular level qualitative data on individual components and interactions can be obtained from the experimental literature and high-throughput technologies, making qualitative approaches such as Boolean network modeling extremely useful. In this paper, we build on our research to provide a methodology overview of Boolean modeling in systems biology, including Boolean dynamic modeling of cellular networks, attractor analysis of Boolean dynamic models, as well as inferring biological regulatory mechanisms from high-throughput data using Boolean models. We finally demonstrate how Boolean models can be applied to perform the structural analysis of cellular networks. This overview aims to acquaint life science researchers with the basic steps of Boolean modeling and its applications in several areas of systems biology.
生物过程的数学建模为复杂的细胞系统提供了深刻的见解。虽然定量和连续的模型（如微分方程）已经被广泛应用，但在那些对机械细节和动力学参数知之甚少的系统中，它们的使用受到了阻碍。另一方面，从实验文献和高通量技术中可以获得大量关于单个组件和相互作用的分子水平定性数据，使得布尔网络建模等定性方法非常有用。在本文中，我们基于我们的研究，提供了系统生物学中布尔建模的方法学概述，包括细胞网络的布尔动态建模、布尔动态模型的吸引子分析，以及使用布尔模型从高通量数据中推断生物调控机制。最后，我们展示了布尔模型如何应用于执行细胞网络的结构分析。该概述旨在使生命科学研究人员了解布尔建模的基本步骤及其在系统生物学几个领域的应用。
