Schwarz Roland, Musch Patrick, von Kamp Axel, Engels Bernd, Schirmer Heiner, Schuster Stefan, Dandekar Thomas
Dept of Bioinformatics, Biocenter, University of Würzburg, Germany.
BMC Bioinformatics. 2005 Jun 1;6:135. doi: 10.1186/1471-2105-6-135.
A number of algorithms for steady state analysis of metabolic networks have been developed over the years. Of these, Elementary Mode Analysis (EMA) has proven especially useful. Despite its low user-friendliness, METATOOL as a reliable high-performance implementation of the algorithm has been the instrument of choice up to now. As reported here, the analysis of metabolic networks has been improved by an editor and analyzer of metabolic flux modes. Analysis routines for expression levels and the most central, well connected metabolites and their metabolic connections are of particular interest.
YANA features a platform-independent, dedicated toolbox for metabolic networks with a graphical user interface to calculate (integrating METATOOL), edit (including support for the SBML format), visualize, centralize, and compare elementary flux modes. Further, YANA calculates expected flux distributions for a given Elementary Mode (EM) activity pattern and vice versa. Moreover, a dissection algorithm, a centralization algorithm, and an average diameter routine can be used to simplify and analyze complex networks. Proteomics or gene expression data give a rough indication of some individual enzyme activities, whereas the complete flux distribution in the network is often not known. As such data are noisy, YANA features a fast evolutionary algorithm (EA) for the prediction of EM activities with minimum error, including alerts for inconsistent experimental data. We offer the possibility to include further known constraints (e.g. growth constraints) in the EA calculation process. The redox metabolism around glutathione reductase serves as an illustration example. All software and documentation are available for download at http://yana.bioapps.biozentrum.uni-wuerzburg.de.
A graphical toolbox and an editor for METATOOL as well as a series of additional routines for metabolic network analyses constitute a new user-friendly software for such efforts.
多年来已开发出多种用于代谢网络稳态分析的算法。其中,基本模式分析(EMA)已证明特别有用。尽管其用户友好性较低,但作为该算法可靠的高性能实现,METATOOL一直是迄今为止的首选工具。如本文所报道,代谢通量模式的编辑器和分析器改进了代谢网络的分析。对表达水平以及最核心、连接良好的代谢物及其代谢连接的分析程序尤为重要。
YANA具有一个与平台无关的专用代谢网络工具箱,带有图形用户界面,可用于计算(集成METATOOL)、编辑(包括对SBML格式的支持)、可视化、集中和比较基本通量模式。此外,YANA可针对给定的基本模式(EM)活性模式计算预期的通量分布,反之亦然。而且,解剖算法、集中算法和平均直径程序可用于简化和分析复杂网络。蛋白质组学或基因表达数据可大致指示某些个体酶的活性,而网络中的完整通量分布通常未知。由于此类数据存在噪声,YANA具有一种快速进化算法(EA),用于以最小误差预测EM活性,包括对不一致实验数据的警报。我们提供了在EA计算过程中纳入进一步已知约束(例如生长约束)的可能性。围绕谷胱甘肽还原酶的氧化还原代谢用作示例。所有软件和文档均可从http://yana.bioapps.biozentrum.uni-wuerzburg.de下载。
一个用于METATOOL的图形工具箱和编辑器以及一系列用于代谢网络分析的附加程序构成了用于此类工作的新的用户友好型软件。