Cootes Adrian P, Muggleton Stephen H, Sternberg Michael J E
Division of Molecular Biosciences, Imperial College London, South Kensington, London SW7 2AZ, UK.
J Mol Biol. 2007 Jun 15;369(4):1126-39. doi: 10.1016/j.jmb.2007.03.013. Epub 2007 Mar 14.
The increasing interest in systems biology has resulted in extensive experimental data describing networks of interactions (or associations) between molecules in metabolism, protein-protein interactions and gene regulation. Comparative analysis of these networks is central to understanding biological systems. We report a novel method (PHUNKEE: Pairing subgrapHs Using NetworK Environment Equivalence) by which similar subgraphs in a pair of networks can be identified. Like other methods, PHUNKEE explicitly considers the graphical form of the data and allows for gaps. However, it is novel in that it includes information about the context of the subgraph within the adjacent network. We also explore a new approach to quantifying the statistical significance of matching subgraphs. We report similar subgraphs in metabolic pathways and in protein-protein interaction networks. The most similar metabolic subgraphs were generally found to occur in processes central to all life, such as purine, pyrimidine and amino acid metabolism. The most similar pairs of subgraphs found in the protein-protein interaction networks of Drosophila melanogaster and Saccharomyces cerevisiae also include central processes such as cell division but, interestingly, also include protein sub-networks involved in pre-mRNA processing. The inclusion of network context information in the comparison of protein interaction networks increased the number of similar subgraphs found consisting of proteins involved in the same functional process. This could have implications for the prediction of protein function.
对系统生物学日益增长的兴趣催生了大量实验数据，这些数据描述了代谢、蛋白质 - 蛋白质相互作用和基因调控中分子间的相互作用（或关联）网络。对这些网络进行比较分析是理解生物系统的核心。我们报告了一种新方法（PHUNKEE：使用网络环境等效性配对子图），通过该方法可以识别一对网络中的相似子图。与其他方法一样，PHUNKEE明确考虑数据的图形形式并允许存在间隙。然而，它的新颖之处在于它包含了相邻网络中子图上下文的信息。我们还探索了一种量化匹配子图统计显著性的新方法。我们报告了代谢途径和蛋白质 - 蛋白质相互作用网络中的相似子图。通常发现最相似的代谢子图出现在所有生命的核心过程中，如嘌呤、嘧啶和氨基酸代谢。在黑腹果蝇和酿酒酵母的蛋白质 - 蛋白质相互作用网络中发现的最相似子图对还包括细胞分裂等核心过程，但有趣的是，还包括参与前体mRNA加工的蛋白质子网。在蛋白质相互作用网络比较中纳入网络上下文信息增加了由参与相同功能过程的蛋白质组成的相似子图的数量。这可能对蛋白质功能的预测有影响。
