Journal
JOURNAL OF STRUCTURAL BIOLOGY
Volume 204, Issue 2, Pages 215-227Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jsb.2018.08.012
Keywords
Cryo-electron microscopy; Single-particle reconstruction; Particle picking; Template-free; Cross-correlation; Micrographs; Support vector machines
Funding
- NIGMS [R01GM090200, P41-GM103311]
- BSF from AFOSR [2014401, FA9550-17-1-0291]
- Simons Investigator Award
- Simons Collaboration on Algorithms and Geometry from Simons Foundation
- Moore Foundation Data-Driven Discovery Investigator Award
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM090200] Funding Source: NIH RePORTER
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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 beta-galactosidase, T20S proteasome, 70S ribosome and keyhole limpet hemocyanin projections.
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