Extracting Disease-Gene-Drug Correlations Based on Data Cube
Wei Xing1,2, Hu Dehua1(), Yi Minhan1, Zhu Qizhen1, Zhu Wenjie2
1Institute of Information Security and Big Data, Central South University, Changsha 410083, China 2School of Basic Courses, Bengbu Medical College, Bengbu 233003, China
[Objective] This study aims to construct a disease-gene-drug correlation network for diabetes mellitus (DM). [Methods] First, we proposed a new data cube-based approach to construct a disease-gene-drug correlations network for the DM. Then, we measured the associations among the biological entities. [Results] We retrieved the needed data from the PubMed database and constructed three 1-D vertex cubes, three 2-D square cubes and one 3-D disease-gene-drug network, which revealed 411 associations among the 14 subclasses of DM, 23 genes, and 24 drugs. We also constructed 8 optimal disease-gene-drug subnetworks of DM. [Limitations] There were some subjective issues with the data analysis. The changing of user behaviors may also influence the results. [Conclusions] The proposed algorithm is better than the existing ones, which provides new directions for research on customized medical treatments.
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