APPLE picker: Automatic particle picking, a low-effort cryo-EM framework

Ayelet Heimowitz, Joakim Andén, Amit Singer

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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 languageEnglish (US)
Pages (from-to)215-227
Number of pages13
JournalJournal of Structural Biology
Volume204
Issue number2
DOIs
StatePublished - 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

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