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Protein-Protein Interaction Networks Alignment using Mathematical Model Approximation

机译:蛋白质 - 蛋白质相互作用网络使用数学模型近似对齐

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The optimal network alignment problem is an NP-hard problem. In this paper, in order to reduce the runtime of solving this problem, an approximated mathematical model is proposed. To be more precise, the similarity matrix of the two networks is used to reduce the number of model's variables. For this purpose, in the proposed approximation model, instead of checking the possibility of alignment of each protein in the first network with every protein in the second one, we only check the alignment of each protein in the first network to the few most similar ones in the second network. At last, in order to solve the proposed approximation model, the Active Set algorithm is used. This new method has been tested on real protein-protein interaction (PPI) networks of different real and synthetic species. Experimental results indicated improvements in the alignment precision of different networks especially large ones in comparison with NETwork ALigner (NETAL) algorithm and also tremendous reduction of running time in comparison with exact model. In addition, the proposed method could achieve desirable precision on synthetic protein-protein networks.
机译:最佳网络对齐问题是NP难题。在本文中,为了减少解决这个问题的运行时间,提出了一种近似的数学模型。更精确地,两个网络的相似性矩阵用于减少模型变量的数量。为此目的,在所提出的近似模型中,除了第二个中的每种蛋白质,我们只检查每个蛋白质中的每种蛋白质在第一网络中对准每个蛋白质的可能性,而不是检查每个蛋白质中的每个蛋白质的对准到最相似的少数在第二个网络中。最后,为了解决所提出的近似模型,使用了活动集算法。这种新方法已经在不同实际和合成物种的实际蛋白质 - 蛋白质相互作用(PPI)网络上进行了测试。实验结果表明,与网络对准器(NERAL)算法相比,不同网络的对准精度的改进,以及与精确模型相比的运行时间的巨大减少。此外,所提出的方法可以在合成蛋白质 - 蛋白质网络上获得理想的精度。

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