论文标题
SuperBubbles是有向网络的经验特征
Superbubbles as an Empirical Characteristic of Directed Networks
论文作者
论文摘要
SuperBubbles是无环诱导的挖掘物，具有单个入口和出口，它们在基因组组装的背景下自然出现以及计算生物学中基因组比对的分析。这些结构可以以线性时间计算，并局限于非对称的挖掘图。我们从经验上证明，从SuperBubbles得出的图参数提供了一种方便的方式，可以区分不同类别的现实图形模型，同时在很大程度上与简单的，常用的参数无关。
Superbubbles are acyclic induced subgraphs of a digraph with single entrance and exit that naturally arise in the context of genome assembly and the analysis of genome alignments in computational biology. These structures can be computed in linear time and are confined to non-symmetric digraphs. We demonstrate empirically that graph parameters derived from superbubbles provide a convenient means of distinguishing different classes of real-world graphical models, while being largely unrelated to simple, commonly used parameters.
