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. 2019 Apr 4;20(Suppl 2):192. doi: 10.1186/s12864-019-5488-5

Fig. 1.

Fig. 1

The deep-learning architecture of MRCNN. The input layer is a matrix of one-hot coding for the DNA fragment centered at the methylation site, and the first convolution layer helps extract the information of each base. Then, it is reshaped as a 2D tensor for the following operations, and the convolution and pooling operations obtain higher-level sequence feature, while the next two convolution layers overcome the side effects of the saturated zone. Finally, the tensor is expanded by the full-connection layer, and the output node gives the prediction value