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pubmed-article:20888965pubmed:abstractTextThe maximum-likelihood method provides a powerful approach to many problems in cryo-electron microscopy (cryo-EM) image processing. This contribution aims to provide an accessible introduction to the underlying theory and reviews existing applications in the field. In addition, current developments to reduce computational costs and to improve the statistical description of cryo-EM images are discussed. Combined with the increasing power of modern computers and yet unexplored possibilities provided by theory, these developments are expected to turn the statistical approach into an essential image-processing tool for the electron microscopist.lld:pubmed
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pubmed-article:20888965pubmed:authorpubmed-author:SigworthFred...lld:pubmed
pubmed-article:20888965pubmed:authorpubmed-author:ScheresSjors...lld:pubmed
pubmed-article:20888965pubmed:authorpubmed-author:DoerschukPete...lld:pubmed
pubmed-article:20888965pubmed:authorpubmed-author:CarazoJose-Ma...lld:pubmed
pubmed-article:20888965pubmed:copyrightInfoCopyright © 2010 Elsevier Inc. All rights reserved.lld:pubmed
pubmed-article:20888965pubmed:issnTypeElectroniclld:pubmed
pubmed-article:20888965pubmed:volume482lld:pubmed
pubmed-article:20888965pubmed:ownerNLMlld:pubmed
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pubmed-article:20888965pubmed:pagination263-94lld:pubmed
pubmed-article:20888965pubmed:dateRevised2011-8-1lld:pubmed
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pubmed-article:20888965pubmed:year2010lld:pubmed
pubmed-article:20888965pubmed:articleTitleAn introduction to maximum-likelihood methods in cryo-EM.lld:pubmed
pubmed-article:20888965pubmed:affiliationDepartment of Cellular and Molecular Physiology, Yale University, New Haven, Connecticut, USA.lld:pubmed
pubmed-article:20888965pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:20888965pubmed:publicationTypeResearch Support, U.S. Gov't, Non-P.H.S.lld:pubmed
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