Exact(3)
2D reference-free alignment and classification was performed using SPIDER (Frank et al., 1996) to generate projection averages.
The SIMIND Monte Carlo program together with the XCAT phantom were used to generate projection data [ 15, 16].
Interestingly, previous in vivo studies suggested that NSCs of the SVZ or parenchymal progenitors expressing the proteoglycan NG2+ may generate projection neurons and interneurons (Magavi et al., 2000; Arvidsson et al., 2002; Nakatomi et al., 2002; Dayer et al., 2005; Gordon et al., 2007; Ernst et al., 2014).
Similar(57)
To explore this possibility, we have used Generalized Ensemble (GE) algorithms [12] to generate projections of the landscape defined by Rosetta's full-atom scoring function.
We used these simulations to generate projections of future changes in temperature and precipitation over the region of interest.
The normalized relative probability for current conditions (nPc) for each sub-model was calculated as:
Images were processed with ImageJ, utilizing either brightest point or average intensity settings to generate projections.
The model results were applied to future climate change situations to generate projections of DF in the 2050s and 2080s.
Series of images were sequentially collected in the Z-axis, and ImageJ software (http://rsbweb.nih.gov/ij/) was used to generate projections for illustrations.
In these simulations, the values of the parameters of the gain-control model found to fit the data in the article (see Table 1) were used to generate projections along the decision axis.
The aim of our work was to develop a Monte Carlo code capable of generating projection images of the human body.
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