circRNA-Disease-association

In this project, we propose a novel computational method based on multi-source information combined with deep convolutional neural network to predict circRNA-disease associations. The method first fuses multi-source information including disease semantic similarity, disease Gaussian interaction profile kernel similarity, and circRNA Gaussian interaction profile kernel similarity, and then extracts its hidden deep feature through the convolutional neural network, and finally sends them to the extreme learning machine classifier for prediction.