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

Nguyen Phuoc NguyenIlker ErsoyJacob GotbergFiliz BunyakTommi A White
Published in: BMC bioinformatics (2021)
DRPnet shows greatly improved time-savings to generate an initial particle dataset compared to manual picking, followed by template-based autopicking. Compared to other networks, DRPnet has equivalent or better performance. DRPnet excels on cryoEM datasets that have low contrast or clumped particles. Evaluating other performance metrics, DRPnet is useful for higher resolution 3D reconstructions with decreased particle numbers or unknown symmetry, detecting particles with better angular orientation coverage.
Keyphrases
  • magnetic resonance
  • high resolution
  • deep learning
  • electron microscopy
  • high throughput
  • magnetic resonance imaging
  • mass spectrometry
  • computed tomography
  • single molecule
  • solar cells