[乳腺癌基因-药物网络模型的构建与分析]
[Construction and analysis of a breast cancer gene-drug network model].
作者信息
Wei Xing, Hu De-Hua, Yi Min-Han, Chang Xue-Lian, Zhu Wen-Jie, Qu Shao-Ling, Deng Duan-Ying
机构信息
1Instituteof Information Security and Big Data, 2School of Public Health,Central South University, Changsha 410083, China; 3Department of Public Courses, Bengbu Medical College, Bengbu 233003, China. E-mail:
出版信息
Nan Fang Yi Ke Da Xue Xue Bao. 2016 Feb;36(2):170-9.
OBJECTIVE
To construct a breast cancer gene-drug network model for extracting and predicting the correlations between breast cancer-related genes and drugs.
METHODS
We developed an algorithm based on the ABC principle and the association rules to obtain the correlations between the biological entities. For breast cancer, we constructed 3 different correlations (gene-gene, drug-drug and gene-drug) and used the R language to implement the associated network model. The reliability of the algorithm was verified by ROC curve.
RESULTS
We identified 185 breast cancer-associated genes and 98 associations between them, 97 drugs and 170 associations between them. The breast cancer genes-drugs network contained 127 genes and 77 drugs with 384 associations between them.
CONCLUSIONS
We identified a large number of different correlations between the breast cancer-related genes and drugs and close correlations between some biological entity pairs that have not yet been reported, which may provide a new strategy for experimental design for testing personalized breast cancer treatment.
目的
构建乳腺癌基因-药物网络模型，以提取和预测乳腺癌相关基因与药物之间的相关性。
方法
我们基于ABC原则和关联规则开发了一种算法，以获得生物实体之间的相关性。对于乳腺癌，我们构建了3种不同的相关性（基因-基因、药物-药物和基因-药物），并使用R语言实现相关的网络模型。通过ROC曲线验证了该算法的可靠性。
结果
我们鉴定出185个乳腺癌相关基因以及它们之间的98个关联，97种药物以及它们之间的170个关联。乳腺癌基因-药物网络包含127个基因和77种药物，它们之间有384个关联。
结论
我们鉴定出大量乳腺癌相关基因与药物之间的不同相关性，以及一些尚未报道的生物实体对之间的紧密相关性，这可能为测试个性化乳腺癌治疗的实验设计提供新策略。
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