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Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

机译:基于蛋白质相互作用网络的蛋白质复合物相关蛋白质-蛋白质相互作用的预测

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A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptivek-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.
机译:提出了一种基于检测到的蛋白质复合物预测蛋白质-蛋白质相互作用的方法,以修复源自高通量生物学实验的相互作用不足。将蛋白质复合物修剪并根据自适应k核方法分解为小部分,以预测与复合物相关的蛋白质-蛋白质相互作用。所提出的方法适用于蛋白质-蛋白质相互作用网络中具有不同结构,数量和节点大小的蛋白质复合物。基于各种算法检测到的不同复杂集,我们可以获得不同的蛋白质相互作用预测集。预测的相互作用集的可靠性通过使用带有统计检验的估计值以及对生物学数据的直接确认来证明。与基于团体预测相互作用的方法相比,预测的重叠很小。同样,从各种复杂集合派生出来的相互作用的预测集合之间的重叠也很小。因此,交互的每个预测的集合可以补充并改善原始网络数据的质量。同时,从所提出的方法的预测仅使用网络拓扑来补充与蛋白质复合物相关的蛋白质-蛋白质相互作用。

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