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we proposed a deep learning based framework, iDeep, to fuse heterogeneous data for predicting RNA-protein interaction sites. The deep learning framework can not only learn the hidden feature patterns from individual source of data, but also extracted the shared representation across them. In addition, the convolutional neural network in iDeep can automatically identify binding motifs. To validate our proposed method over other methods, we perform experiments on large-scale CLIP-seq datasets. The comprehensive results indicated the huge advantage of iDeep, which performs much better than the state-of-the-art methods.