Functional annotation from predicted protein interaction networks
Functional annotation from predicted protein interaction networks
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DOI：
10.1093/bioinformatics/bti514
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发表时间：
2005-08-01
期刊：
影响因子：
5.8
通讯作者：
Samudrala, R
中科院分区：
文献类型：
--
作者：
McDermott, J;Bumgarner, R;Samudrala, R
动机：在大规模实验测定几种生物的蛋白质-蛋白质相互作用网络的进展导致了基于网络连接性的功能推断的创新方法。然而，大量的努力和资源所需的实验蛋白质相互作用网络的阐明是禁止的。在此之前，我们和其他人，已经开发出技术来预测蛋白质相互作用的新基因组使用计算方法和其他genomes.Results产生的数据：我们评估了基于网络的功能注释方法，使我们预测的蛋白质相互作用网络的性能。我们表明，这种方法在实验推导和预测的交互网络上表现同样出色，手动和计算分配的注释。我们将该方法应用于预测来自所有生命领域的超过50种生物的蛋白质相互作用网络，为许多以前未注释的蛋白质提供注释并验证现有的低置信度注释。可用性：超过50种生物的功能预测可在http://bioverse.compbio.washington.edu获得，用于分析的数据集可在http://data.compbio.washington.edu/misc/downloads/nannotation_data/Contact：admin@bioverse.compbio.华盛顿. edu补充信息：补充附录提供了正文中没有的额外细节。(http：//data.compbio.washington.edu/misc/downloads/nannotation_data/download.pdf）。
Motivation: Progress in large-scale experimental determination of protein-protein interaction networks for several organisms has resulted in innovative methods of functional inference based on network connectivity. However, the amount of effort and resources required for the elucidation of experimental protein interaction networks is prohibitive. Previously we, and others, have developed techniques to predict protein interactions for novel genomes using computational methods and data generated from other genomes.Results: We evaluated the performance of a network-based functional annotation method that makes use of our predicted protein interaction networks. We show that this approach performs equally well on experimentally derived and predicted interaction networks, for both manually and computationally assigned annotations. We applied the method to predicted protein interaction networks for over 50 organisms from all domains of life, providing annotations for many previously unannotated proteins and verifying existing low-confidence annotations.Availability: Functional predictions for over 50 organisms are available at http://bioverse.compbio.washington.edu and datasets used for analysis at http://data.compbio.washington.edu/misc/downloads/nannotation_data/Contact: admin@bioverse.compbio.washington.eduSupplementary information: A supplemental appendix gives additional details not in the main text. (http://data.compbio.washington.edu/misc/downloads/nannotation_data/supplement.pdf).