Predicting side effects of drugs is a critical issue for the drug discovery.

We transform approved drugs, side effect terms and drug–side effect associations as a recommender system.

We design two recommender methods, i.e. the integrated neighborhood-based method and the restricted Boltzmann machine-based method, to make predictions.

Further, we combine proposed methods and existing methods of the same type to develop ensemble models.