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Using design of experiment procedures, variation was systematically introduced, and the effects of this variation were analyzed using regression models.
Moreover, there are both direct and indirect effects of this variation.
Human genomes show extensive genetic variation across individuals, but we have only just started documenting the effects of this variation on the regulation of gene expression.
Further prospective research, with larger numbers of participants and fully confounding risk factors considered, such as age, sex, ethnicity and life style, is warrant to examine the possible effects of this variation on T2DM to confirm our conclusion.
It is possible that variation at this locus has modest effects on T2DM, but environmental factors may predominate in the progress of T2DM, and mask the effects of this variation.
While the variability of individual logR values is large, due to variances in PCR conditions and primer sequences, modified algorithms such as that of Nannya and coworkers [7] and the Illumina proprietary method, as well as the application of a moving average, are available to reduce the effects of this variation across a chromosomal region.
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This model explores the effect of this variation on somatic EPSPs and dendritic spike initiation, as compared to the case of uniform AMPA and NMDA conductance.
The effect of this variation in K as the gas passes down the line is examined.
Currently, designers attempt to reduce the effect of this variation for each specification; however, the specification spreads are much larger than that of their earlier counterparts.
The effect of this variation in temperature is also investigated and it is observed that higher temperature does not have any significant impact on system efficiency.
A side-effect of this variation is that straightforward estimates of b-value above, say, the minimum magnitude m0 = 2.15, may not work well in the EEPAS model.
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