Assessment of prediction accuracy of protein function from protein-protein interaction data
Assessment of prediction accuracy of protein function from protein-protein interaction data
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作者：
Hishigaki, H;Nakai, K;Takagi, T
基因组开放阅读框的功能预测是酵母基因组学研究的重要内容之一。在许多大规模的实验中，确定蛋白质与蛋白质之间的相互作用是特别重要的，因为相互作用的蛋白质通常具有相同的功能。因此，当蛋白质相互作用伴侣的功能已知时，似乎可以预测蛋白质的功能。然而，体外实验经常受到人为因素的影响，并且蛋白质通常可以具有具有不同功能的多个结合伴侣。我们开发了一种客观的预测方法，可以系统地包括间接相互作用的信息。我们的方法可以预测酵母蛋白的亚细胞定位，细胞作用和生化功能的准确率分别为72.7%，63.6%和52.7%。预测精度上升的蛋白质与三个以上的结合伙伴，因此我目前的开放预测结果为16个这样的蛋白质。版权所有（C）2001约翰威利父子有限公司
Functional prediction of open reading frames coded in the genome is one of the most important tasks in yeast genomics. Among a number of large-scale experiments for assigning certain functional classes to proteins, experiments determining protein-protein interaction are especially important because interacting proteins usually have the same function. Thus, it seems possible to predict the function of a protein when the function of its interacting partner is known. However, in vitro experiments often suffer from artifacts and a protein can often have multiple binding partners with different functions. We developed an objective prediction method that can systematically include the information of indirect interaction. Our method can predict the subcellular localization, the cellular role and the biochemical function of yeast proteins with accuracies of 72.7%, 63.6% and 52.7%, respectively. The prediction accuracy rises for proteins with more than three binding partners and thus me present the open prediction results for 16 such proteins. Copyright (C) 2001 John Wiley & Sons, Ltd.