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Published on: April 6, 2016
[Construction and analysis of a breast cancer gene-drug network model]
Xing Wei1, De-Hua Hu, Min-Han Yi
11Instituteof 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.
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.
