Flow Model of the Protein-protein Interaction Network for Finding Credible Interactions

Kinya Okada, K. Asai, Masanori Arita
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引用次数: 2

Abstract

Large-scale protein-protein interactions (PPIs) detected by yeast-two-hybrid (Y2H) systems are known to contain many false positives. The separation of credible interactions from background noise is still an unavoidable task. In the present study, we propose the relative reliability score for PPI as an intrinsic characteristic of global topology in the PPI networks. Our score is calculated as the dominant eigenvector of an adjacency matrix and represents the steady state of the network flow. By using this reliability score as a cut-off threshold from noisy Y2H PPI data, the credible interactions were extracted with better or comparable performance of previously proposed methods which were also based on the network topology. The result suggests that the application of the network-flow model to PPI data is useful for extracting credible interactions from noisy experimental data.
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寻找可信相互作用的蛋白质-蛋白质相互作用网络流模型
酵母-双杂交(Y2H)系统检测到的大规模蛋白质-蛋白质相互作用(PPIs)已知含有许多假阳性。从背景噪声中分离可信相互作用仍然是一个不可避免的任务。在本研究中,我们提出PPI的相对可靠性评分作为PPI网络全局拓扑的内在特征。我们的分数被计算为邻接矩阵的主要特征向量,并表示网络流的稳定状态。通过使用该可靠性评分作为噪声Y2H PPI数据的截止阈值,可以提取出与先前提出的基于网络拓扑的方法具有更好或相当性能的可信交互。结果表明,将网络流模型应用于PPI数据有助于从噪声实验数据中提取可信的相互作用。
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