Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, Connecticut, USA.
Nat Methods. 2011 Feb;8(2):177-83. doi: 10.1038/nmeth.1546. Epub 2010 Dec 26.
Managing the overwhelming numbers of molecular states and interactions is a fundamental obstacle to building predictive models of biological systems. Here we introduce the Network-Free Stochastic Simulator (NFsim), a general-purpose modeling platform that overcomes the combinatorial nature of molecular interactions. Unlike standard simulators that represent molecular species as variables in equations, NFsim uses a biologically intuitive representation: objects with binding and modification sites acted on by reaction rules. During simulations, rules operate directly on molecular objects to produce exact stochastic results with performance that scales independently of the reaction network size. Reaction rates can be defined as arbitrary functions of molecular states to provide powerful coarse-graining capabilities, for example to merge Boolean and kinetic representations of biological networks. NFsim enables researchers to simulate many biological systems that were previously inaccessible to general-purpose software, as we illustrate with models of immune system signaling, microbial signaling, cytoskeletal assembly and oscillating gene expression.
管理大量的分子状态和相互作用是构建生物系统预测模型的一个基本障碍。在这里,我们介绍了无网络随机模拟器(NFsim),这是一个通用的建模平台,克服了分子相互作用的组合性质。与将分子物种表示为方程中的变量的标准模拟器不同,NFsim 使用了一种生物学上直观的表示方法:具有结合和修饰位点的对象,受反应规则的作用。在模拟过程中,规则直接作用于分子对象,产生精确的随机结果,其性能与反应网络大小无关。反应速率可以定义为分子状态的任意函数,以提供强大的粗粒度能力,例如合并生物网络的布尔和动力学表示。NFsim 使研究人员能够模拟许多以前无法使用通用软件访问的生物系统,我们将通过免疫系统信号、微生物信号、细胞骨架组装和振荡基因表达的模型来说明这一点。