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It is seen that this variance is bounded by values less than 1 even in lattices of dimensions 2048×2048.
The component score plot for component 1 (Figure S2A) shows that this variance arises from differences in the electronic transition occurring mainly in the carboxylate groups, a fact that may arise from structural variability among heparin preparations.
As all of the probes in this plot are specific for the same transcript, we assume that this variance cannot be due to true differences in transcript abundance, but to an artifact of sequence differences.
Note that this variance is assumed constant for all pairwise treatment comparisons.
We have shown that this variance increases during gestation (Gielen et al. 2007).
These results led us to hypothesize that this variance resulted from decreases in oxygen tension in cultures not undergoing agitation.
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Meta-regression analysis was developed to deal with this problem, by pinpointing variables that contribute to this variance.
Wade and Stevens showed that increasing this variance, as would happen because of drift or if infection appeared in a subset of the groups, raised the invasion threshold and reduced the per-generation change in average infection frequency across groups.
This is because there was considerable genetic and environmental variance in the pathways through which people attained any given level of education, and it was possible that some of this variance overlapped with that in BMI.
The proportion of this variance that is explained by genetic factors is equivalent to the proportion of variance in initiation explained by genetic factors, and similarly for the environmental factors.
We have found that much of this variance may be attributed to ambient variation in the isotopic composition of the base of the food web.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com