Sentence examples for bases of variability from inspiring English sources

Exact(1)

That is, over the range 9 to 68 (60 bases of variability) all positions had the same gap surprisal of GS d) = -log2(1/60) = 5.91 bits according to equation (2).

Similar(59)

However, according to the data of Gerner-Smidt, based on variability of 16S rDNA the differences between Lautropia mirabilis and Burkholderia cepacia were 7.7% [ 6], which can characterize the higher resolution features of gltB gene sequences.

We assessed population variability for given physiologic profiles and breast-feeding history using Monte Carlo simulations based on variability of three independent sensitive parameters (breast milk consumption, fraction of lipids in breast milk, and fraction of lipids in infant adipose tissue).

Expected values were estimated based on variability of gene expression between G9ac ntr or Ezh2 cntr RNAseq samples.

The % CV, based on variability of cAMP concentrations in vehicle-treated cardiomyocytes, was 12% and therefore increases in cAMP formation of 36% or more are detectable in this assay (Table 4 ).

An additional advantage of the approach taken in the current study is that it allowed us to gain insight into the neural bases of individual variability in beat perception and sensorimotor synchronization.

Hoffman, P., Lambon Ralph, M. & Rogers, T. Semantic diversity: a measure of semantic ambiguity based on variability in the contextual usage of words.

The following gait domains are used: Rhythm, Pace, Phases, Base of Support, Variability, Tandem, and Turn.

In order to elucidate the genomic bases of the significant variability exhibited by environmental strains of the symbiotic phenotype, we sequenced the genomes of two strains of S. meliloti, AK83 and BL225C.

Previous studies have posited that the rate of adaptation in a given environment is determined by Bayesian sensorimotor integration based on the amount of variability in the state of the environment.

Unlike the classical methods this technique adaptively adjusts the segmentation criterion based on the degree of variability in neighboring regions of the image.

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