Automated analysis of information processing, kinetic independence and modular architecture in biochemical networks using MIDIA.
Automated analysis of information processing, kinetic independence and modular architecture in biochemical networks using MIDIA.
复制标题
使用 MIDIA 对生化网络中的信息处理、动力学独立性和模块化架构进行自动分析。
DOI：
10.1093/bioinformatics/btq694
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Bowsher CG
中科院分区：
文献类型：
--
作者：
Bowsher CG
动机：理解生物化学反应网络的信息编码和传播，以及这些信息处理特性与模块化网络结构的关系，在细胞信号传导和调节的研究中具有根本的重要性。然而，一个严格的，自动化的方法，一般的生化网络还没有，高通量分析，因此一直遥不可及。结果：模块化识别的动态独立算法（MIDIA）是一个用户友好的，可扩展的R包，进行自动化分析的信息是如何处理的生化网络。一个重要的组成部分是该算法的能力，以确定准确的网络分解的基础上的质量行动动力学和网络的信息属性。这些模块化使用树结构可视化，从中可以直接读取重要的动态条件独立属性。只有部分化学计量信息需要被用作输入MIDIA，既不需要模拟，也不需要速率参数的知识。例如，当应用于信令网络时，该方法识别在其多个输入和输出之间的信息的顺序传播中涉及的路由和种类。这些路线对应于树结构中的相关路径，并且可以使用输入-输出路径矩阵工具进一步可视化。MIDIA在计算上仍然适用于目前可用的最大网络重建，并且可以直接与系统生物学标记语言（SBML）编写的模型一起使用。可用性：该软件包在GNU通用公共许可证下分发，并且可以在http://code.google.com/p/midia上与可浏览的补充材料链接一起使用。更多信息请访问www.maths.bris.ac.uk/~macgb/Software.html.Contact:C.Bowsher@bristol.ac.ukSupplementary信息：补充材料包含MIDIA软件包的详细描述，可在Bioinformaticsonline上获得。
Motivation:Understanding the encoding and propagation of information by biochemical reaction networks and the relationship of such information processing properties to modular network structure is of fundamental importance in the study of cell signalling and regulation. However, a rigorous, automated approach for general biochemical networks has not been available, and high-throughput analysis has therefore been out of reach.Results:Modularization Identification by Dynamic Independence Algorithms (MIDIA) is a user-friendly, extensible R package that performs automated analysis of how information is processed by biochemical networks. An important component is the algorithm's ability to identify exact network decompositions based on both the mass action kinetics and informational properties of the network. These modularizations are visualized using a tree structure from which important dynamic conditional independence properties can be directly read. Only partial stoichiometric information needs to be used as input to MIDIA, and neither simulations nor knowledge of rate parameters are required. When applied to a signalling network, for example, the method identifies the routes and species involved in the sequential propagation of information between its multiple inputs and outputs. These routes correspond to the relevant paths in the tree structure and may be further visualized using the Input–Output Path Matrix tool. MIDIA remains computationally feasible for the largest network reconstructions currently available and is straightforward to use with models written in Systems Biology Markup Language (SBML).Availability:The package is distributed under the GNU General Public License and is available, together with a link to browsable Supplementary Material, at http://code.google.com/p/midia. Further information is at www.maths.bris.ac.uk/~macgb/Software.html.Contact:C.Bowsher@bristol.ac.ukSupplementary information:The Supplementary Material contains extensive description of the MIDIA package and is available atBioinformaticsonline.