论文标题
在彩色图中的主题上
On motifs in colored graphs
论文作者
论文摘要
生物网络分析中最重要的概念之一是网络图案,它们是在给定网络中以高于随机网络中预期的频率中发生的互连模式。在这项工作中,我们有兴趣在一类可以用顶点色图表示的生物网络中搜索和推断网络图案。我们显示了许多与多彩拓扑主题相关的问题的计算复杂性,并为特殊情况提供了有效的算法。我们还提出了一种概率策略,以检测顶点图中高度频繁的基序。实际数据集的实验表明,我们的算法在效率和解决方案的质量方面都非常有竞争力。
One of the most important concepts in biological network analysis is that of network motifs, which are patterns of interconnections that occur in a given network at a frequency higher than expected in a random network. In this work we are interested in searching and inferring network motifs in a class of biological networks that can be represented by vertex-colored graphs. We show the computational complexity for many problems related to colorful topological motifs and present efficient algorithms for special cases. We also present a probabilistic strategy to detect highly frequent motifs in vertex-colored graphs. Experiments on real data sets show that our algorithms are very competitive both in efficiency and in quality of the solutions.