Linked Life Data

15808859

Source:http://linkedlifedata.com/resource/pubmed/id/15808859

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2005-4-5
pubmed:abstractText
A maximum-likelihood approach to multi-reference image refinement is presented. In contrast to conventional cross-correlation refinement, the new approach includes a formal description of the noise, implying that it is especially suited to cases with low signal-to-noise ratios. Application of this approach to a cryo-electron microscopy dataset revealed two major classes for projections of simian virus 40 large T-antigen in complex with an asymmetric DNA-probe, containing the origin of simian virus 40 replication. Strongly bent projections of dodecamers showed density that may be attributed to the complexed double-stranded DNA, while almost straight projections revealed a twist in the relative orientation of the hexameric subunits. This new level of detail for large T-antigen projections was not detected using conventional techniques. For a negative stain dataset, maximum-likelihood refinement yielded results that were practically identical to those obtained using conventional multi-reference refinement. Results obtained using simulated data suggest that the efficiency of the maximum-likelihood approach may be further enhanced by explicitly incorporating the microscope contrast transfer function in the image formation model.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
0022-2836
pubmed:author
pubmed:issnType
Print
pubmed:day
22
pubmed:volume
348
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
139-49
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Maximum-likelihood multi-reference refinement for electron microscopy images.
pubmed:affiliation
Biocomputing Unit, Centro Nacional de Biotecnología, Campus Universidad Autónoma, Cantoblanco, 28049, Madrid, Spain.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't