MDA-TOEPGA: A novel method to identify miRNA-disease association based on two-objective evolutionary programming genetic algorithm

[摘要] The association between miRNA and disease has attracted more and more attention. Until now, existing methodsfor identifying miRNA related disease mainly rely on top-ranked association model, which may not provide a full landscapeof association between miRNA and disease. Hence there is strong need of new computational method to identify theassociations from miRNA group view. In this paper, we proposed a framework, MDA-TOEPGA, to identify miRNAdisease association based on two-objective evolutionary programming genetic algorithm, which identifies latent miRNAdisease associations from the view of functional module. To understand the miRNA functional module in diseases, thecase study is presented. We have been compared MDA-TOEPGA with several state-of-the-art functional modulealgorithm. Experimental results showed that our method cannot only outperform classical algorithms, such as K-means,IK-means, MCODE, HC-PIN, and ClusterONE, but can also achieve an ideal overall performance in terms of acomposite score consisting of f1, Sensitivity, and Accuracy. Altogether, our study showed that MDA-TOEPGA is apromising method to investigate miRNA-disease association from the landscapes of functional module.

[学科分类] 仪器

[关键词] MiRNA functional module;MiRNA-disease association;Two-objective;Evolutionary programming genetic algorithm