<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Baxter, Bill</style></author><author><style face="normal" font="default" size="100%">Grassucci, Robert A</style></author><author><style face="normal" font="default" size="100%">Gao, Haixiao</style></author><author><style face="normal" font="default" size="100%">Frank, Joachim</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Determination of signal-to-noise ratios and spectral SNRs in cryo-EM low-dose imaging of molecules.</style></title><secondary-title><style face="normal" font="default" size="100%">J Struct Biol</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J. Struct. Biol.</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Cryoelectron Microscopy</style></keyword><keyword><style  face="normal" font="default" size="100%">Image Processing, Computer-Assisted</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year><pub-dates><date><style  face="normal" font="default" size="100%">05/2009</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/19269332</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">166</style></volume><pages><style face="normal" font="default" size="100%">126-32</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;&lt;span style=&quot;font-family: arial, helvetica, clean, sans-serif; font-size: 13px; line-height: 17px;&quot;&gt;Attempts to develop efficient classification approaches to the problem of heterogeneity in single-particle reconstruction of macromolecules require phantom data with realistic noise models. We have estimated the signal-to-noise ratios and spectral signal-to-noise ratios for three steps in the electron microscopic image formation from data obtained experimentally. An important result is that structural noise, i.e., the irreproducible component of the object prior to image formation, is substantial, and of the same order of magnitude as the reproducible signal. Based on this result, the noise modeling for testing new classification techniques can be improved.&lt;/span&gt;&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue></record></records></xml>