Bayesian inference of initial models in cryo-electron microscopy using pseudo-atoms.

ABSTRACT: Single-particle cryo-electron microscopy is widely used to study the structure of macromolecular assemblies. Tens of thousands of noisy two-dimensional images of the macromolecular assembly viewed from different directions are used to infer its three-dimensional structure. The first step is to estimate a low-resolution initial model and initial image orientations. This is a challenging global optimization problem with many unknowns, including an unknown orientation for each two-dimensional image. Obtaining a good initial model is crucial for the success of the subsequent refinement step. We introduce a probabilistic algorithm for estimating an initial model. The algorithm is fast, has very few algorithmic parameters, and yields information about the precision of estimated model parameters

SUBMITTER: Joubert P 

PROVIDER: S-EPMC4375433 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature