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Detalle de: Fast maximum-likelihood refinement of electron microscopy images

Title Fast maximum-likelihood refinement of electron microscopy images
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

Apa Reference Scheres, S.H., Valle, M. & Carazo, J. (2005). Fast maximum-likelihood refinement of electron microscopy images. Bioinformatics, 21(suppl_2), ii243-ii244. 10.1093/bioinformatics/bti1140
Doi 10.1093/bioinformatics/bti1140
Publication Date 1 Sep 2005
Publication Type Article
Researcher Jose María Salvador Carazo Garcia
Ontology Structural bioinformatics, Experimental structure determination, Image analysis, Cryo-electron microscopy
Research Groups
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