Prediction of RNA Structures with Pseudoknots Using Convolutional Neural Network
To get better predicted results, we show using convolution neural network inference RNA structure with pseudoknots. First, we expound the deep learning and convolution model and algorithm of the neural network theory, then discuss the key problems for RNA secondary structure prediction using convolution neural network modeling, finally, we design a convolutional neural network to predict RNA structure prediction model and experimental verification of the validity of the model, and the experimental results show that the convolution neural network in the prediction of RNA sequence structure has long-range correlation, can improve the prediction accuracy, especially when RNA sequences with pseudoknots structure.
KeywordsConvolution neural network RNA Structure prediction
This work was supported by Scientific Research Projects (No. 15C0204) of Hunan Education Department and supported by the Science and Technology Plan Project of Hunan Province (2016TP1020). Application-oriented Special Disciplines, Double First-Class University Project of Hunan Province (Xiangjiaotong  469).
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