The structure of the deep learning method contains two parts: the embedding module and task specific module. In the embedding module, RNA sequences of fixed lengths were converted into a numeric matrix vector and used as an input for the task specific module. The task specific module contains a CNN layer for extracting features, a max-pooling layer for speeding up the computation, BLSTM and attention layers, and fully connect layer for output result.