2018Heimowitz ApplePicker

Citation

Heimowitz, A., Andén, J. & Singer, A. APPLE Picker: Automatic Particle Picking, a Low-Effort Cryo-EM Framework. Journal of Structural Biology, 2018, 204(2), 215-227.

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 beta-galactosidase, T20S proteasome, 70S ribosome and keyhole limpet hemocyanin projections.

Links

https://www.ncbi.nlm.nih.gov/pubmed/30134153

Related software

https://github.com/PrincetonUniversity/APPLEpicker

https://github.com/PrincetonUniversity/APPLEpicker-python