A topological measurement for weighted protein interaction network.

Pengjun Pei, Aidong Zhang
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引用次数: 39

Abstract

High-throughput methods for detecting protein-protein interactions (PPI) have given researchers an initial global picture of protein interactions on a genomic scale. The usefulness of this understanding is, however, typically compromised by noisy data. The effective way of integrating and using these non-congruent data sets has received little attention to date. This paper proposes a model to integrate different data sets. We construct this model using our prior knowledge of data set reliability. Based on this model, we propose a topological measurement to select reliable interactions and to quantify the similarity between two proteins' interaction profiles. Our measurement exploits the small-world network topological properties of protein interaction network. Meanwhile, we discovered some additional properties of the network. We show that our measurement can be used to find reliable interactions with improved performance and to find protein pairs with higher function homogeneity.

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加权蛋白质相互作用网络的拓扑测量方法。
检测蛋白质-蛋白质相互作用(PPI)的高通量方法为研究人员提供了基因组尺度上蛋白质相互作用的初步全局图像。然而,这种理解的有用性通常会受到噪声数据的影响。如何有效地整合和利用这些非同余数据集,目前还没有得到足够的重视。本文提出了一种集成不同数据集的模型。我们使用我们对数据集可靠性的先验知识来构建这个模型。基于该模型,我们提出了一种拓扑测量方法来选择可靠的相互作用,并量化两种蛋白质相互作用谱之间的相似性。我们的测量利用了蛋白质相互作用网络的小世界网络拓扑特性。同时,我们还发现了该网络的一些附加特性。我们表明,我们的测量可以用来找到可靠的相互作用,提高性能,并找到具有更高功能同质性的蛋白质对。
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Tree decomposition based fast search of RNA structures including pseudoknots in genomes. An algebraic geometry approach to protein structure determination from NMR data. A tree-decomposition approach to protein structure prediction. A pivoting algorithm for metabolic networks in the presence of thermodynamic constraints. A topological measurement for weighted protein interaction network.
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