Bioinformatics Original Paper Predicting Interactions in Protein Networks by Completing Defective Cliques
Bioinformatics Original Paper Predicting Interactions in Protein Networks by Completing Defective Cliques
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DOI：
10.1016/j.cor.2009.06.024
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发表时间：
2010-04
期刊：
影响因子：
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通讯作者：
Haiyuan Yu;A. Paccanaro;Valery Trifonov;M. Gerstein
中科院分区：
文献类型：
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作者：
Haiyuan Yu;A. Paccanaro;Valery Trifonov;M. Gerstein
通过检测蛋白质-蛋白质相互作用的大规模、高通量方法获得的数据集通常受到相对较高水平的噪声的影响。我们描述了一种新的方法，通过预测错过的蛋白质-蛋白质相互作用，只使用大规模实验观察到的蛋白质相互作用网络的拓扑，来提高这些数据集的质量。该方法的中心思想是搜索蛋白质相互作用网络中的缺陷集团(两两相互作用的蛋白质的几乎完全的复合体)，并预测完成它们的相互作用。我们给出了将该方法应用于大规模网络的算法，并在实践中证明了该方法的有效性和良好的预测性能。更多信息可在我们的网站上找到
Datasets obtained by large-scale, high-throughput methods for detecting protein–protein interactions typically suffer from a relatively high level of noise. We describe a novel method for improving the quality of these datasets by predicting missed protein–protein interactions, using only the topology of the protein interaction network observed by the large-scale experiment. The central idea of the method is to search the protein interaction network for defective cliques (nearly complete complexes of pairwise interacting proteins), and predict the interactions that complete them. We formulate an algorithm for applying this method to large-scale networks, and show that in practice it is efficient and has good predictive performance. More information can be found on our website