Format

Send to

Choose Destination
Bioinformatics. 2005 Sep 1;21 Suppl 2:ii243-4.

Fast maximum-likelihood refinement of electron microscopy images.

Author information

1
Centro Nacional de Biotecnología-CSIC, Campus Universidad Autónoma, Madrid, Spain.

Abstract

MOTIVATION:

Maximum-likelihood (ML) image refinement is a promising candidate to improve attainable resolution limits in 3D-EM. However, its large CPU requirements may prohibit application to 3D-structure optimization.

RESULTS:

We speeded up ML image refinement by reducing its search space over the alignment parameters. Application of this reduced-search approach to a cryo-EM dataset yielded practically identical results as the original approach, but in approximately one day instead of one week of CPU.

AVAILABILITY:

This work has been implemented in the public domain package Xmipp. Documentation and download instructions may be found at: http://www.cnb.uam.es/~bioinfo

PMID:
16204112
DOI:
10.1093/bioinformatics/bti1140
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Silverchair Information Systems
Loading ...
Support Center