Abstract
Particle picking is a crucial first step in the computational pipeline of single-particle cryo-electron microscopy (cryo-EM). Selecting particles from the micrographs is difficult especially for small particles with low contrast. As high-resolution reconstruction typically requires hundreds of thousands of particles, manually picking that many particles is often too time-consuming. While template-based particle picking is currently a popular approach, it may suffer from introducing manual bias into the selection process. In addition, this approach is still somewhat time-consuming. This paper presents the APPLE (Automatic Particle Picking with Low user Effort) picker, a simple and novel approach for fast, accurate, and template-free particle picking. This approach is evaluated on publicly available datasets containing micrographs of β-galactosidase, T20S proteasome, 70S ribosome and keyhole limpet hemocyanin projections.
Original language | English (US) |
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Pages (from-to) | 215-227 |
Number of pages | 13 |
Journal | Journal of Structural Biology |
Volume | 204 |
Issue number | 2 |
DOIs | |
State | Published - Nov 2018 |
All Science Journal Classification (ASJC) codes
- Structural Biology
Keywords
- Cross-correlation
- Cryo-electron microscopy
- Micrographs
- Particle picking
- Single-particle reconstruction
- Support vector machines
- Template-free