Sentence examples for estimate to explain from inspiring English sources

This evaluation consists of two components, assessing the capacity of a common variance estimate to explain the observed gene sample variances and evaluating how improving this common variance estimate can aid in the detection of differentially expressed genes.

In order to assess the capacity of a common variance estimate to explain the observed gene sample variances we will use the shrinkage coefficient λ, described in the methods section, as a statistic.

The researchers wrote that > Most notably, the diversity in mutation rate of single nucleotide polymorphisms is dominated by the age of the father at conception of the child… After accounting for random Poisson variation, father's age is estimated to explain nearly all of the remaining variation in the de novo mutation counts.

First, Mincer earnings equations are estimated to explain the log wages of men and women.

A bivariate probit model, estimated to explain the different types of technological innovations (product and/or process), shows that firms with strategic CSR profiles are more likely to innovate in both products and processes.

Improved mental health, measured through lower levels of depression, was estimated to explain nearly 30percentt of the benefit from living around green spaces.

However, none of the newly identified loci is estimated to explain more than 1% of the heritability.

One notable exception is the apolipoprotein E locus (APOE): the ε4 allele is common, increases AD susceptibility 3-fold, and is estimated to explain at least 10% of the population-attributable risk of disease [1].

For instance, the SNP in the HMGA2 gene region is estimated to explain 0.3% of the variation in height, and the average increase per risk allele is 0.4 cm.

The mapped locus in chromosome 17 was named belr1 locus (berghei liver resistance) and the genetic effect of the highest linked marker (D17Mit20) was estimated to explain 15.4% of phenotypic variance observed in the F2 progeny.

Even with our relatively large sample size, our power to detect a variant similar to the 15q25.1 SNP rs1051730 (which was estimated to explain about 0.7% of the trait variance [44] at the genome-wide significance level) was only 8.5% for the combined analysis (and less than 1% for either study alone).