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Prediction of protein phenotype based on protein interaction network by coupling genetic algorithm and K-nearest neighbor algorithm

机译:遗传算法和K-最近邻算法相结合的基于蛋白质相互作用网络的蛋白质表型预测

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摘要

Quick and accurate identification of protein phenotype is a key step for understanding life at the molecular level, and has a significant impact in the fields of biomedicine and pharmacy. However, as a result of genome and other sequencing projects, there is a huge gap between the number of discovered proteins and the number of phenotype annotated proteins. Therefore, it is indispensable to develop an automated and reliable method for predicting protein phenotype. In this paper, a novel method is proposed and used to identify protein phenotype. It is featured by coupling the genetic algorithm and K-nearest neighbor algorithm, and the feature vector is introduced to take into account the information of the protein and the neighboring proteins in the protein interaction network. As a demonstration, a fivefold cross-validation test and independent test set are performed, and the results indicate that the current method may serve as an important complementary tool for other existing algorithms in this area. The source code of MATLAB is freely available on request from the authors.
机译:快速准确地鉴定蛋白质表型是从分子水平理解生命的关键步骤,并且在生物医学和药学领域具有重要影响。但是,由于基因组和其他测序项目的结果,发现的蛋白质数量与带表型注释的蛋白质数量之间存在巨大差距。因此,开发一种自动可靠的方法来预测蛋白质表型是必不可少的。本文提出了一种新的方法,用于识别蛋白质表型。通过结合遗传算法和K-最近邻算法进行特征化,并引入特征向量以考虑蛋白质相互作用网络中蛋白质及其邻近蛋白质的信息。作为演示,执行了五重交叉验证测试和独立测试集,结果表明,当前方法可以作为该领域其他现有算法的重要补充工具。作者可根据要求免费获取MATLAB的源代码。

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