Sentence examples for ems data set from inspiring English sources

We counted the number of days from the Monday of the first official week of the autumn/winter A(H1N1) influenza pandemic as outlined in the reference data to the first day with a signal in the respective EMS data set.[ 37] A second approach took into consideration the amount of time required to collect and process the reference and syndromic surveillance data (reporting delay, see Table  2).

The second EM data set focused on secreted amino acid measurements from a separate study of yeast cultured in different ammonium and potassium concentrations [ 33].

Similar to the negative stain analysis, class averages from the cryo-EM data set revealed that the majority of particles are early intermediates.

The first EM data set compares wild type yeast to the gdh1/GDH2 (glutamate dehydrogenase) strain [ 31], which indicated good agreement between predicted metabolic changes of intracellular metabolite levels and fluxes [ 31, 32].

Putative 3′-domain classes are enriched in the degraded sample 1, while Group II classes are enriched in the intact sample 2. DOI: http://dx.doi.org/10.7554/eLife.04491.016 10.7554/eLiFigure91.017 Figure 6 figure supplement 2. 3D classification of Group I particles from cryo-EM data set of affinity-purified sample.

For cryo-EM data sets, beam-induced motion correction was performed as previously described (Li et al., 2013).

We analysed a large number of randomly recorded low-magnification EM data sets of HTLV-1-infected (Figure 1A) and uninfected (Figure 1B) CD4+ T cells.

This refinement process fails, however, when a large number of particle images with poor SNR are used, that is, typical cryo-EM data sets of small molecules.

A powerful method of dealing with structural heterogeneity in cryo-EM data sets is to 'focus' refinement on a defined region of the protein complex of interest.

Alignment and classification of images in both 2D and 3D are key methods for improving SNR and detection and sorting of heterogeneity in EM data sets.

However, the process of grid optimisation, data collection and processing of cryo-EM data sets lead to a longer experimental time frame than for the negative stain microscopy approach detailed here.