Systems Biology Group, Life Sciences Research Unit, University of Luxembourg, Belvaux, Luxembourg.
Bioinformatics. 2017 Nov 1;33(21):3431-3436. doi: 10.1093/bioinformatics/btx380.
Mathematical modelling of regulatory networks allows for the discovery of knowledge at the system level. However, existing modelling tools are often computation-heavy and do not offer intuitive ways to explore the model, to test hypotheses or to interpret the results biologically.
We have developed a computational approach to contextualize logical models of regulatory networks with biological measurements based on a probabilistic description of rule-based interactions between the different molecules. Here, we propose a Matlab toolbox, FALCON, to automatically and efficiently build and contextualize networks, which includes a pipeline for conducting parameter analysis, knockouts and easy and fast model investigation. The contextualized models could then provide qualitative and quantitative information about the network and suggest hypotheses about biological processes.
FALCON is freely available for non-commercial users on GitHub under the GPLv3 licence. The toolbox, installation instructions, full documentation and test datasets are available at https://github.com/sysbiolux/FALCON. FALCON runs under Matlab (MathWorks) and requires the Optimization Toolbox.
Supplementary data are available at Bioinformatics online.
调控网络的数学建模允许在系统层面上发现知识。然而,现有的建模工具通常计算量很大,并且没有提供直观的方法来探索模型、测试假设或从生物学角度解释结果。
我们开发了一种计算方法,基于规则交互的概率描述,将调控网络的逻辑模型与生物测量数据联系起来。在这里,我们提出了一个 Matlab 工具箱 FALCON,用于自动且高效地构建和关联网络,其中包括一个进行参数分析、敲除以及快速简便的模型研究的管道。上下文化的模型随后可以为网络提供定性和定量信息,并提出关于生物过程的假设。
FALCON 根据 GPLv3 许可证在 GitHub 上免费提供给非商业用户。工具箱、安装说明、完整文档和测试数据集可在 https://github.com/sysbiolux/FALCON 上获得。FALCON 在 Matlab(MathWorks)下运行,需要优化工具箱。
补充数据可在《Bioinformatics》在线获得。