Department of Bioengineering, Rice University, Houston, TX, USA.
Bioinformatics. 2011 Jul 15;27(14):1957-63. doi: 10.1093/bioinformatics/btr271. Epub 2011 May 5.
A metabolic graph represents the connectivity patterns of a metabolic system, and provides a powerful framework within which the organization of metabolic reactions can be analyzed and elucidated. A common practice is to prune (i.e. remove nodes and edges) the metabolic graph prior to any analysis in order to eliminate confounding signals from the representation. Currently, this pruning process is carried out in an ad hoc fashion, resulting in discrepancies and ambiguities across studies.
We propose a biochemically informative criterion, the strength of chemical linkage (SCL), for a systematic pruning of metabolic graphs. By analyzing the metabolic graph of Escherichia coli, we show that thresholding SCL is powerful in selecting the conventional pathways' connectivity out of the raw network connectivity when the network is restricted to the reactions collected from these pathways. Further, we argue that the root of ambiguity in pruning metabolic graphs is in the continuity of the amount of chemical content that can be conserved in reaction transformation patterns. Finally, we demonstrate how biochemical pathways can be inferred efficiently if the search procedure is guided by SCL.
代谢图表示代谢系统的连接模式，并提供了一个强大的框架，可在其中分析和阐明代谢反应的组织。在进行任何分析之前，通常会修剪（即删除节点和边）代谢图，以消除表示中的混杂信号。目前，此修剪过程是临时进行的，导致不同研究之间存在差异和歧义。
我们提出了一种基于生化信息的标准，即化学连接强度（SCL），用于系统地修剪代谢图。通过分析大肠杆菌的代谢图，我们表明，当网络仅限于从这些途径收集的反应时，将 SCL 阈值化可有效地选择常规途径的连接性，而不是原始网络连接性。此外，我们认为修剪代谢图中的歧义根源在于反应转化模式中可以保守的化学含量的连续性。最后，我们展示了如果通过 SCL 指导搜索过程，如何有效地推断生化途径。
