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进化分析表明,低覆盖率是蛋白质相互作用网络比对面临的主要挑战。

Evolutionary analysis reveals low coverage as the major challenge for protein interaction network alignment.

作者信息

Ali Waqar, Deane Charlotte M

机构信息

Department of Statistics, 1 South Parks Road, Oxford, UKOX1 3TG.

出版信息

Mol Biosyst. 2010 Nov;6(11):2296-304. doi: 10.1039/c004430j. Epub 2010 Aug 26.

Abstract

Local alignments of protein interaction networks have found little conservation among several species. While this could be a consequence of the incompleteness of interaction data-sets and presence of error, an intriguing prospect is that the process of network evolution is sufficient to erase any evidence of conservation. Here, we aim to test this hypothesis using models of network evolution and also investigate the role of error in the results of network alignment. We devised a distance metric based on summary statistics to assess the fit between experimental and simulated network alignments. Our results indicate that network evolution alone is unlikely to account for the poor quality alignments given by real data. Alignments of simulated networks undergoing evolution are considerably (4 to 5 times) larger than real alignments. We compare several error models in their ability to explain this discrepancy. Our estimates of false negative rates vary from 20 to 60% dependent on whether incomplete proteome sampling is taken into account or not. We also find that false positives appear to affect network alignments little compared to false negatives indicating that incompleteness, not spurious links, is the major challenge for interactome-level comparisons.

摘要

蛋白质相互作用网络的局部比对在多个物种间几乎未发现保守性。虽然这可能是由于相互作用数据集不完整以及存在误差导致的,但一个有趣的可能性是网络进化过程足以消除任何保守性的证据。在此,我们旨在使用网络进化模型来检验这一假设,并研究误差在网络比对结果中的作用。我们基于汇总统计量设计了一种距离度量,以评估实验性和模拟性网络比对之间的契合度。我们的结果表明,仅网络进化不太可能解释实际数据给出的低质量比对。经历进化的模拟网络的比对结果比实际比对结果大得多(4到5倍)。我们比较了几种误差模型解释这种差异的能力。我们对假阴性率的估计在20%到60%之间,这取决于是否考虑了不完整的蛋白质组采样。我们还发现,与假阴性相比,假阳性似乎对网络比对的影响很小,这表明不完整性而非虚假链接是相互作用组水平比较的主要挑战。

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