Sentence examples for principal variability in from inspiring English sources

Not surprisingly, our experiments identified that the age of the donor accounted for the principal variability in the data.

The peak time reduction in the control group after treatment supposedly arises from the principal variability of this electrophysiologic method.

Using this method we show in details the sensitivity of the grating couplers to the principal fabrication variabilities in order to maximize the robustness of the design.

Warm-core (anti-cyclonic) rings that spin off the Gulf Stream are the principal source of variability in slope waters, and introduce water with different properties into the major slope water masses in the upper 1000 m [20].

PCs are the eigenvectors of the covariance matrix of X (101-dimensional), and capture the different principal patterns of variability in the original waveform data.

4) A similar issue comes up in the section on neural network modeling, which shows that chosen-value effects in the simulation can be explained away by a principal component capturing variability in neural dynamics, but doesn't state clearly enough that "dynamics" here refers, not just to latency, but to a mixture of amplitude and latency.

The main source of variability in the data (principal component 1 and 2; > 71% of the variance) corresponded to time-related expression changes that reflect chronological vascular development11.

Among bacterial species, INDELs have been identified as the principal source of genome variability in Mycobacterium tuberculosis complex [ 15].

To take into account the effect of population structure on evolutionary rate, we used SNV data across the strains to estimate principal components contributing to variability in the strains (Sato et al., 2005).

To identify the main source of variability in our microarray data, we performed principal component analysis (PCA) and analysis of variance distribution across our datasets.

Principal component analysis allows for the determination of those genes having the greatest influence on the variability in one principal component by rank ordering the loading values of that principal component.