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Relevance judgment algorithm for detecting protein complexes from protein interaction networks

机译:从蛋白质相互作用网络中检测蛋白质复合物的相关性判断算法

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In protein-protein interaction networks, proteins combine into macromolecular complexes to execute essential functions in the cells, such as replication, transcription, protein transport. To solve the problem of detecting protein complexes from protein interaction networks, we use relevant graph and irrelevant graph to represent the relation of connection between a node and a core graph. We define a variable Relevancy to represent whether a node has a dense or loose connection to a core graph. Then we propose the Relevancy Judgment algorithm to detecting protein complexes from protein interaction networks. Our algorithm decides whether a node belongs to a protein complex through judging the relevancy between core graph and nodes out of core graph. Experiment results show that our algorithm has an excellent performance in both accuracy and hit rate.
机译:在蛋白质-蛋白质相互作用网络中,蛋白质结合成大分子复合物以在细胞中执行基本功能,例如复制,转录,蛋白质转运。为了解决从蛋白质相互作用网络中检测蛋白质复合物的问题,我们使用相关图和不相关图来表示节点和核心图之间的连接关系。我们定义一个变量“相关性”来表示节点与核心图的连接是密集的还是松散的。然后,我们提出了相关性判断算法,用于从蛋白质相互作用网络中检测蛋白质复合物。我们的算法通过判断核心图与核心图之外的节点之间的相关性来确定节点是否属于蛋白质复合物。实验结果表明,该算法在准确性和命中率方面均具有优异的性能。

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