Graph Theoretic and Pearson Correlation-Based Discovery of Network Biomarkers for Cancer
Graph Theoretic and Pearson Correlation-Based Discovery of Network Biomarkers for Cancer
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DOI：
10.3390/data4020081
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发表时间：
2019-06
期刊：
影响因子：
2.6
通讯作者：
R. Tanvir;Tasmia Aqila;Mona Maharjan;Abdullah Al Mamun;A. Mondal
中科院分区：
文献类型：
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作者：
R. Tanvir;Tasmia Aqila;Mona Maharjan;Abdullah Al Mamun;A. Mondal
两个图论的概念-团和二分图-探索在基因网络水平上识别癌症的网络生物标志物。基本原理是一组基因通过形成一个簇或一个类似于细胞的结构来共同工作，
Two graph theoretic concepts—clique and bipartite graphs—are explored to identify the network biomarkers for cancer at the gene network level. The rationale is that a group of genes work together by forming a cluster or a clique-like structures to initiat