Detection of functional gene-gene interactions from observational gene expression data using classifier ensembles and Metalearning

This study investigated how to take a joint advantage of two promising approaches: Ensemble of Classifiers and Metalearning in the prediction of functional gene-gene interactions from observational gene expression data. This problem is of great value in medical research, but very challenging due to the randomness of the biological systems, the elevated noise levels of the data and the high dimensionalities involved.