DRPnet: automated particle picking in cryo-electron micrographs using deep regression.

ABSTRACT:

Background

Identification and selection of protein particles in cryo-electron micrographs is an important step in single particle analysis. In this study, we developed a deep learning-based particle picking network to automatically detect particle centers from cryoEM micrographs. This is a challenging task due to the nature of cryoEM data, having low signal-to-noise ratios with variable particle sizes, shapes, distributions, grayscale variations as well as other undesirable artifacts.

Results

We propose a double convolutional neural network (CNN) cascade for automated detection of particles in cryo-electron micrographs. This approach, entitled Deep Regression Picker Network or "DRPnet", is simple but very effective in recognizing different particle sizes, shapes, distributio

SUBMITTER: Nguyen NP 

PROVIDER: S-EPMC7869254 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature