Literature DB >> 15065679

Classical detection theory and the cryo-EM particle selection problem.

Fred J Sigworth1.   

Abstract

Particle selection is an essential but tedious step in the determination of macromolecular structures by single particle reconstruction. This paper presents an automatic, multi-reference particle detection scheme that is based on the classical matched filter principle. It makes use of a pre-whitening filter to standardize the noise, a reduced representation of the references by means of principal component analysis, and a statistic for distinguishing particles from image artifacts. Standardizing the noise allows the noise-induced false-positive frequency to be estimated, and also allows the distribution of the discrimination statistic to be calculated a priori. The method is demonstrated with an annotated dataset of cryo-EM images.

Mesh:

Substances:

Year:  2004        PMID: 15065679     DOI: 10.1016/j.jsb.2003.10.025

Source DB:  PubMed          Journal:  J Struct Biol        ISSN: 1047-8477            Impact factor:   2.867


  22 in total

Review 1.  Single-particle cryo-electron microscopy of macromolecular complexes.

Authors:  Georgios Skiniotis; Daniel R Southworth
Journal:  Microscopy (Oxf)       Date:  2015-11-25       Impact factor: 1.571

2.  Automatic particle selection from electron micrographs using machine learning techniques.

Authors:  C O S Sorzano; E Recarte; M Alcorlo; J R Bilbao-Castro; C San-Martín; R Marabini; J M Carazo
Journal:  J Struct Biol       Date:  2009-06-23       Impact factor: 2.867

3.  A clarification of the terms used in comparing semi-automated particle selection algorithms in cryo-EM.

Authors:  Robert Langlois; Joachim Frank
Journal:  J Struct Biol       Date:  2011-03-21       Impact factor: 2.867

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

Authors:  Ayelet Heimowitz; Joakim Andén; Amit Singer
Journal:  J Struct Biol       Date:  2018-08-19       Impact factor: 2.867

5.  Reference-free particle selection enhanced with semi-supervised machine learning for cryo-electron microscopy.

Authors:  Robert Langlois; Jesper Pallesen; Joachim Frank
Journal:  J Struct Biol       Date:  2011-06-17       Impact factor: 2.867

6.  Structural basis of bacterial σ28 -mediated transcription reveals roles of the RNA polymerase zinc-binding domain.

Authors:  Wei Shi; Wei Zhou; Baoyue Zhang; Shaojia Huang; Yanan Jiang; Abigail Schammel; Yangbo Hu; Bin Liu
Journal:  EMBO J       Date:  2020-06-02       Impact factor: 11.598

7.  Efficient Extraction of Macromolecular Complexes from Electron Tomograms Based on Reduced Representation Templates.

Authors:  Xiao-Ping Xu; Christopher Page; Niels Volkmann
Journal:  Comput Anal Images Patterns       Date:  2015-08-25

8.  Computing steerable principal components of a large set of images and their rotations.

Authors:  Colin Ponce; Amit Singer
Journal:  IEEE Trans Image Process       Date:  2011-05-02       Impact factor: 10.856

9.  Automatic cryo-EM particle selection for membrane proteins in spherical liposomes.

Authors:  Yunhui Liu; Fred J Sigworth
Journal:  J Struct Biol       Date:  2014-01-24       Impact factor: 2.867

10.  Introducing robustness to maximum-likelihood refinement of electron-microscopy data.

Authors:  Sjors H W Scheres; José María Carazo
Journal:  Acta Crystallogr D Biol Crystallogr       Date:  2009-06-20
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.