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A Novel Protein Complex Identification Algorithm Based on Connected Affinity Clique Extension (CACE)

机译:基于连接亲和群扩展(CACE)的新型蛋白质复合物识别算法

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摘要

A novel algorithm based on Connected Affinity Clique Extension (CACE) for mining overlapping functional modules in protein interaction network is proposed in this paper. In this approach, the value of protein connected affinity which is inferred from protein complexes is interpreted as the reliability and possibility of interaction. The protein interaction network is constructed as a weighted graph, and the weight is dependent on the connected affinity coefficient. The experimental results of our CACE in two test data sets show that the CACE can detect the functional modules much more effectively and accurately when compared with other state-of-art algorithms CPM and IPC-MCE.
机译:提出了一种基于连接亲和性集团扩展(CACE)的新算法,用于挖掘蛋白质相互作用网络中重叠的功能模块。在这种方法中,从蛋白复合物推断出的蛋白连接亲和力的值被解释为相互作用的可靠性和可能性。蛋白质相互作用网络被构建为加权图,并且权重取决于连接的亲和系数。我们的CACE在两个测试数据集中的实验结果表明,与其他最新算法CPM和IPC-MCE相比,CACE可以更有效,更准确地检测功能模块。

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