Deep learning methods for protein torsion angle prediction.

Journal: BMC bioinformatics
Published Date:

Abstract

BACKGROUND: Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins.

Authors

  • Haiou Li
    Department of Computer Science and Technology, Soochow University, Suzhou, Jiangsu, 215006, China.
  • Jie Hou
    Department of Computer Science, University of Missouri, Columbia, MO, 65211, USA.
  • Badri Adhikari
    Department of Computer Science, University of Missouri, Columbia, MO 65211, USA.
  • Qiang Lyu
    Department of Computer Science and Technology, Soochow University, Suzhou, Jiangsu, 215006, China.
  • Jianlin Cheng
    Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA.