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Functional evaluation of domain-domain interactions and human protein interaction networks

机译:域-域相互作用和人类蛋白质相互作用网络的功能评估

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Motivation: Large amounts of protein and domain interaction data are being produced by experimental high-throughput techniques and computational approaches. To gain insight into the value of the provided data, we used our new similarity measure based on the Gene Ontology (GO) to evaluate the molecular functions and biological processes of interacting proteins or domains. The applied measure particularly addresses the frequent annotation of proteins or domains with multiple GO terms. Results: Using our similarity measure, we compare predicted domain-domain and human protein-protein interactions with experimentally derived interactions. The results show that our similarity measure is of significant benefit in quality assessment and confidence ranking of domain and protein networks. We also derive useful confidence score thresholds for dividing domain interaction predictions into subsets of low and high confidence.
机译:动机:实验高通量技术和计算方法正在产生大量的蛋白质和域相互作用数据。为了深入了解所提供数据的价值,我们使用了基于基因本体论(GO)的新相似性度量来评估相互作用的蛋白质或域的分子功能和生物学过程。所应用的措施特别解决了经常使用多个GO词条注释蛋白质或结构域的问题。结果:使用我们的相似性度量,我们将预测的域-域和人蛋白质-蛋白质相互作用与实验得出的相互作用进行了比较。结果表明,我们的相似性度量在质量评估以及域和蛋白质网络的置信度排序方面具有显着优势。我们还导出了有用的置信度得分阈值,用于将域交互预测分为低和高置信度子集。

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