癌症蛋白在人类蛋白-蛋白相互作用网络中的中心地位:重访。

Q4 Pharmacology, Toxicology and Pharmaceutics
Wei Xiong, Luyu Xie, Shuigeng Zhou, Hui Liu, Jihong Guan
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引用次数: 14

摘要

蛋白质-蛋白质相互作用(PPI)网络的拓扑分析已广泛应用于癌症机制的研究。然而,与人类PPI网络中的其他蛋白质相比,癌症蛋白是否表现出更多的拓扑中心性仍存在争议。为了解决这一争论,我们首先确定了四组人类蛋白质,然后通过同源基因将这些蛋白质映射到酵母PPI网络中。最后,我们比较了这些蛋白在人和酵母PPI网络中的特性。在两个真实数据集上的实验表明,癌蛋白比非癌蛋白具有更高的聚类程度和更小的聚类系数。实验结果还证实,与STRING数据集上的其他蛋白质相比,癌症蛋白具有更大的中间性中心性。然而,在BioGRID数据集上,癌症蛋白的平均中间度中心性大于疾病和控制蛋白,但小于必需蛋白。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The centrality of cancer proteins in human protein-protein interaction network: a revisit.

Topological analysis of protein-protein interaction (PPI) networks has been widely applied to the investigation on cancer mechanisms. However, there is still a debate on whether cancer proteins exhibit more topological centrality compared to the other proteins in the human PPI network. To resolve this debate, we first identified four sets of human proteins, and then mapped these proteins into the yeast PPI network by homologous genes. Finally, we compared these proteins' properties in human and yeast PPI networks. Experiments over two real datasets demonstrated that cancer proteins tend to have higher degree and smaller clustering coefficient than non-cancer proteins. Experimental results also validated that cancer proteins have larger betweenness centrality compared to the other proteins on the STRING dataset. However, on the BioGRID dataset, the average betweenness centrality of cancer proteins is larger than that of disease and control proteins, but smaller than that of essential proteins.

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来源期刊
International Journal of Computational Biology and Drug Design
International Journal of Computational Biology and Drug Design Pharmacology, Toxicology and Pharmaceutics-Drug Discovery
CiteScore
1.00
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