English

Adaptive nonparametric detection in cryo-electron microscopy

Applications 2013-12-02 v1 Methodology Machine Learning

Abstract

Cryo-electron microscopy (cryo-EM) is an emerging experimental method to characterize the structure of large biomolecular assemblies. Single particle cryo-EM records 2D images (so-called micrographs) of projections of the three-dimensional particle, which need to be processed to obtain the three-dimensional reconstruction. A crucial step in the reconstruction process is particle picking which involves detection of particles in noisy 2D micrographs with low signal-to-noise ratios of typically 1:10 or even lower. Typically, each picture contains a large number of particles, and particles have unknown irregular and nonconvex shapes.

Cite

@article{arxiv.1311.7650,
  title  = {Adaptive nonparametric detection in cryo-electron microscopy},
  author = {Mikhail Langovoy and Michael Habeck and Bernhard Schoelkopf},
  journal= {arXiv preprint arXiv:1311.7650},
  year   = {2013}
}

Comments

Proceedings of the 58-th World Statistical Congress (2011)

R2 v1 2026-06-22T02:17:44.644Z