| Literature DB >> 26682015 |
Joakim Andén1, Eugene Katsevich2, Amit Singer1.
Abstract
Classifying structural variability in noisy projections of biological macromolecules is a central problem in Cryo-EM. In this work, we build on a previous method for estimating the covariance matrix of the three-dimensional structure present in the molecules being imaged. Our proposed method allows for incorporation of contrast transfer function and non-uniform distribution of viewing angles, making it more suitable for real-world data. We evaluate its performance on a synthetic dataset and an experimental dataset obtained by imaging a 70S ribosome complex.Entities:
Keywords: 3D reconstruction; Cryo-EM; classification; conjugate gradient; covariance; heterogeneity; single particle reconstruction; structural variability
Year: 2015 PMID: 26682015 PMCID: PMC4679407 DOI: 10.1109/ISBI.2015.7163849
Source DB: PubMed Journal: Proc IEEE Int Symp Biomed Imaging ISSN: 1945-7928