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Identification of lung cancer associated protein by clique percolation clustering analysis

机译:Clique渗滤聚类分析鉴定肺癌相关蛋白质

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Identification of cancer associated proteins is the crucial problem in cancer research. Recently various techniques have been developed to discover novel cancer genes/proteins. Topological network of protein-protein interaction with their gene ontology annotation are good predictors of cancer proteins. Protein-protein interaction information has provided a basis for studying the cancer cellular network. In this study, we implemented clique percolation clustering approach on lung cancer protein-protein interaction information to identify cancer associated proteins, the enriched protein biological function in molecular networks of the clique motif and also the enriched KEGG pathways were observed.
机译:癌症相关蛋白质的鉴定是癌症研究的关键问题。最近已经开发了各种技术来发现新型癌症基因/蛋白质。蛋白质 - 蛋白质与其基因本体的拓扑网络是癌症蛋白质的良好预测因子。蛋白质 - 蛋白质相互作用信息为研究癌症蜂窝网络提供了基础。在这项研究中,我们在肺癌蛋白 - 蛋白质相互作用信息上实施了Clique渗透聚类方法,以鉴定癌症相关蛋白质,在Clique Motif的分子网络中富集的蛋白质生物学功能以及富集的Kegg途径。

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