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首页> 外文期刊>Journal of cellular physiology. >Network-based integration method for potential breast cancer gene identification
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Network-based integration method for potential breast cancer gene identification

机译：基于网络的集成方法的潜力乳腺癌基因鉴定

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摘要

Breast cancer is the most common female death-causing cancer worldwide. A network-based integration method was proposed to identify potential breast cancer genes. First, genes were prioritized using a gene prioritization algorithm by the strategy of disease risks transferred between genes in a network with weighted vertexes and edges. Our prioritization algorithm was effectives and robust for top-ranked seed gene number and higher area under the curve values compared to ToppGene and ToppNet. Then, 20 potential breast cancer genes were identified as common genes of the top 50 candidate genes for their robustness in multiple prioritizations. These genes could accurately classify tumor and normal samples of all and paired sample sets and three independent datasets. Of potential breast cancer genes, 18 were verified by literature and 2 were novel genes that need further study. This study would contribute to the understanding of the genetic architecture for the diagnosis and treatment of breast cancer.
机译：乳腺癌是最常见的女性death-causing全球癌症。提出了集成方法来识别潜在的乳腺癌基因。优先使用基因优先级算法疾病风险的战略转移之间的基因与加权网络中顶点和边。有生力量和强劲的顶级种子基因数量和更高的曲线下的面积值相比ToppGene ToppNet。被确定为潜在的乳腺癌基因前50名的共同基因的候选基因他们在多个优先级的鲁棒性。这些基因可以准确地分类肿瘤正常的所有样品和配对样本集和三个独立的数据集。癌症基因,18个被文学和验证2小说基因,需要进一步研究。研究将有助于理解基因诊断和架构治疗乳腺癌。

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