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A Protein-Protein Interaction Prediction Method Embracing Intra-Protein Domain Cohesion Information

机译:一种蛋白质 - 蛋白质相互作用预测方法,其具有蛋白质域内的内核信息

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Recently, many computational methods for predicting protein-protein interaction (PPI) have been developed by utilizing domain-domain interaction or associated information. However, most of the methods lack of reflecting the collaboration effect of multiple domains to the prediction of PPL In this paper, we develop a computational model that considers not only inter relationship between protein pair but also the intra-domain functional cohesion effect in PPI. In the computational model, a value assigning method to reflect the intra and inter collaboration devised and the computed values are stored in Interaction Significance (IS) matrix. Then an equation for PPI prediction is devised on IS matrix. For S. cerevisiae PPI data from DIP, MINT and IntAct, domain data from Pfam-A, the prediction method achieved 73.91% and 92.02% sensitivity and specificity respectively.
机译:最近,通过利用域域相互作用或相关信息,已经开发了许多用于预测蛋白质 - 蛋白质相互作用(PPI)的计算方法。然而,大多数方法缺乏反映多个域对本文预测PPL的协作效果,我们开发了一种计算模型,其不仅考虑了蛋白质对之间的关​​系,而且考虑了PPI中的域内功能内聚作用。在计算模型中,以反映设计的帧内和协作和计算值的值分配方法存储在交互意义(是)矩阵中。然后设计了PPI预测的等式是矩阵。对于来自倾角,薄荷和完整的PPI数据,来自PFAM-A的域数据,预测方法分别实现了73.91%和92.02%的灵敏度和特异性。

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