Enhanced prediction of RNA solvent accessibility with long short-term memory neural networks and improved sequence profiles.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: The de novo prediction of RNA tertiary structure remains a grand challenge. Predicted RNA solvent accessibility provides an opportunity to address this challenge. To the best of our knowledge, there is only one method (RNAsnap) available for RNA solvent accessibility prediction. However, its performance is unsatisfactory for protein-free RNAs.

Authors

  • Saisai Sun
    School of Mathematical Sciences, Nankai University, Tianjin, China.
  • Qi Wu
    Endoscopy Center, Peking University Cancer Hospital and Institute, Beijing, China.
  • Zhenling Peng
    Center for Applied Mathematics, Tianjin University, Tianjin, China.
  • Jianyi Yang
    School of Mathematical Sciences, Nankai University, Tianjin, China.