Blinov Michael L, Faeder James R, Goldstein Byron, Hlavacek William S
Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
Bioinformatics. 2004 Nov 22;20(17):3289-91. doi: 10.1093/bioinformatics/bth378. Epub 2004 Jun 24.
BioNetGen allows a user to create a computational model that characterizes the dynamics of a signal transduction system, and that accounts comprehensively and precisely for specified enzymatic activities, potential post-translational modifications and interactions of the domains of signaling molecules. The output defines and parameterizes the network of molecular species that can arise during signaling and provides functions that relate model variables to experimental readouts of interest. Models that can be generated are relevant for rational drug discovery, analysis of proteomic data and mechanistic studies of signal transduction.
BioNetGen允许用户创建一个计算模型,该模型可表征信号转导系统的动力学,并全面、精确地说明特定的酶活性、潜在的翻译后修饰以及信号分子结构域之间的相互作用。其输出定义并参数化了信号传导过程中可能出现的分子种类网络,并提供了将模型变量与感兴趣的实验读数相关联的功能。所生成的模型与合理的药物发现、蛋白质组学数据分析以及信号转导的机制研究相关。