Prediction of RNA Structures with Pseudoknots Using Convolutional Neural Network

  • Sixin TangEmail author
  • Shiting Li
  • Jing Chen
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1143)


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.


Convolution 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 [2018] 469).


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© Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  1. 1.College of Computer Science and Technology, Hengyang Normal UniversityHengyangChina

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