Name
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 Contact: carazo@cnb.uam.es |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1093/bioinformatics/bti1140 | ECCB/JBI |
Keywords | Field | DocType |
maximum likelihood,electron microscopy,public domain,search space | Data mining,Computer science,Maximum likelihood,Documentation | Conference |
Volume | Issue | ISSN |
21 | 2 | 1367-4803 |
Citations | PageRank | References |
3 | 0.77 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sjors H. W. Scheres | 1 | 3 | 0.77 |
| Mikel Valle | 2 | 4 | 1.14 |
| J M Carazo | 3 | 49 | 4.08 |