DeepCryoPicker: fully automated deep neural network for single protein particle picking in cryo-EM.

Journal: BMC bioinformatics
Published Date: Nov 9, 2020

Abstract

BACKGROUND: Cryo-electron microscopy (Cryo-EM) is widely used in the determination of the three-dimensional (3D) structures of macromolecules. Particle picking from 2D micrographs remains a challenging early step in the Cryo-EM pipeline due to the diversity of particle shapes and the extremely low signal-to-noise ratio of micrographs. Because of these issues, significant human intervention is often required to generate a high-quality set of particles for input to the downstream structure determination steps.

Authors

  • Adil Al-Azzawi
    Electrical Engineering and Computer Science Department, University of Missouri, Columbia, MO, 65211, USA.
  • Anes Ouadou
    Electrical Engineering and Computer Science Department, University of Missouri, Columbia, MO, 65211, USA.
  • Highsmith Max
    Electrical Engineering and Computer Science Department, University of Missouri, Columbia, MO, 65211, USA.
  • Ye Duan
    Beijing Key Laboratory of Bioprocess, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.
  • John J Tanner
    Departments of Biochemistry and Chemistry, University of Missouri, Columbia, MO, 65211-2060, USA.
  • Jianlin Cheng
    Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, USA.

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