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Inferring Strengths of Protein-Protein Interactions Using Support Vector Regression

机译:使用支持载体回归推断蛋白质 - 蛋白质相互作用的强度

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Protein-protein interactions (PPIs) play various important roles in living organisms. Hence, many efforts have been made to investigate and predict PPIs. Analysis of strengths of PPIs is important as well as PPIs because such strengths are involved in functionality of proteins. In this paper, we propose several feature space mappings from protein pairs, which make use of protein domain information, and perform five-fold cross-validation for data obtained from biological experiments. The result of average root mean square error (RMSE) using support vector regression (SVR) with our proposed feature was better than that by the best existing method, APM proposed by Chen et al.
机译:蛋白质 - 蛋白质相互作用(PPI)在生物体中发挥各种重要作用。因此,已经进行了许多努力来调查和预测PPI。 PPI强度分析很重要,因为这种优点涉及蛋白质的功能。在本文中,我们提出了来自蛋白质对的几个特征空间映射,这是利用蛋白质结构域信息,并对从生物实验中获得的数据进行五倍的交叉验证。使用支持向量回归(SVR)的平均根均线误差(RMSE)的结果优于Chen等人的最佳现有方法,优于最佳现有方法。

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