Sentence examples for Test transformation from inspiring English sources

Exact(1)

Triplicate reactions were performed for each transformant.> -wrap-foot> Underegionsregindicateicate restriction enzyme sites The master Ti vector pPK2BarGFPD [ 23] containing the phosphinothricin resistant bar marker, was employed to test transformation efficiency of M. thermophila mediated by A. tumefaciens.

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The results suggest that t-test transformation of tree-ignorant metrics can be sufficient to control for patterns arising from shared ancestry.

The statistical significance of coevolution metrics between alignment columns separated by a specified distance was determined using the t-test transformation.

We have argued, and our results demonstrate, the t-test transformation provides sufficient control for the shared ancestry cause of associations.

Using a novel t-test transformation of coevolution metrics, we systematically compared four tree-aware and five tree-ignorant coevolution algorithms, applying them to myoglobin and myosin.

Although the coevolutionary scores are not directly comparable between the methods, the t-test transformation standardizes the metrics, allowing evaluation of the relative performance of each method.

If (q(x)) contains two or more regular singular points, then the oscillatory properties of the solutions can still be investigated across each singularity by applying a different (x=f(t)) transformation in each interval that contains one such singularity.

Furthermore, the fundamental symmetry of nature, expressed by the CPT theorem, requires all of the laws of physics to be the same under simultaneous C, P, and T transformations.

In the operator case the formula for a rank two transformation of the spectral measure is derived and it appears to be the t-transformation of a probability measure, studied previously in the free probability context.

For all a, b > 0, define m π t ( a, b ) = ∏ n = 1 ∞ m ( a t n, b t n ) (3). which we call the t-transformation of m.

The corresponding P value were ascertained by t-transformation, t = |R| ∙ [(N - 2) / (1 - R2)]½, treating the result as coming from a t distribution with N-2 degrees of freedom [ 70].

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