用腔方法对齐图和寻找子结构
Aligning graphs and finding substructures by a cavity approach
摘要：
我们介绍了一个新的分布式算法对齐图或找到一个给定的图内的子结构。它是在腔方法的基础上发展起来的，用来研究随机图的最大团和图对齐问题。该算法允许分析大型图，并可能在计算生物学等领域中找到应用。作为一个概念的证明，我们使用我们的算法来对齐的相似性图的两个相互作用的蛋白质家族参与细菌信号转导，并预测实际上这些家庭之间的相互作用的蛋白质伴侣。
英文摘要：
We introduce a new distributed algorithm for aligning graphs or finding substructures within a given graph. It is based on the cavity method and is used to study the maximum-clique and the graph-alignment problems in random graphs. The algorithm allows to analyze large graphs and may find applications in fields such as computational biology. As a proof of concept we use our algorithm to align the similarity graphs of two interacting protein families involved in bacterial signal transduction, and to predict actually interacting protein partners between these families.
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