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PPIevo: Protein-protein interaction prediction from PSSM based evolutionary information

机译：PPIevo：基于PSSM的进化信息预测蛋白质-蛋白质相互作用

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摘要

Protein-protein interactions regulate a variety of cellular processes. There is a great need for computational methods as a complement to experimental methods with which to predict protein interactions due to the existence of many limitations involved in experimental techniques. Here, we introduce a novel evolutionary based feature extraction algorithm for protein-protein interaction (PPI) prediction. The algorithm is called PPIevo and extracts the evolutionary feature from Position-Specific Scoring Matrix (PSSM) of protein with known sequence. The algorithm does not depend on the protein annotations, and the features are based on the evolutionary history of the proteins. This enables the algorithm to have more power for predicting protein-protein interaction than many sequence based algorithms. Results on the HPRD database show better performance and robustness of the proposed method. They also reveal that the negative dataset selection could lead to an acute performance overestimation which is the principal drawback of the available methods.
机译：蛋白质-蛋白质相互作用调节多种细胞过程。由于实验技术存在许多局限性，因此迫切需要计算方法作为对预测蛋白质相互作用的实验方法的补充。在这里，我们介绍一种用于蛋白质-蛋白质相互作用（PPI）预测的新颖的基于进化的特征提取算法。该算法称为PPIevo，可从具有已知序列的蛋白质的特定位置评分矩阵（PSSM）中提取进化特征。该算法不依赖于蛋白质注释，其特征基于蛋白质的进化历史。与许多基于序列的算法相比，这使该算法具有更大的预测蛋白质相互作用的能力。 HPRD数据库上的结果表明，该方法具有更好的性能和鲁棒性。他们还揭示了负面的数据集选择可能导致严重的性能高估，这是可用方法的主要缺点。

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