Sentence examples for using a uniform model from inspiring English sources

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Using a uniform model to assess this variance will yield false positives that are enriched for genes which have high variance in biological replicates.

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The contribution of repulsive interactions between adsorbed molecules to the surface stress is explored using a uniform compression model.

The researchers, using a uniform disk model, determined that Betelgeuse had a diameter of 0.047 arcseconds, although the stellar disk was likely 17% larger due to the limb darkening, resulting in an estimate for its angular diameter of about 0.055".

In each selected school, we randomly selected a class in grades 6 7 and one class in grades 8 9 using a uniform probability model.

The current BitSeq implementation contains the option of using a uniform read density model or using the model proposed by Roberts et al. (2011) which can account for positional and sequence bias.

This paper presents steady state and pseudo-steady state productivity equations for an off-center partially penetrating vertical well in an anisotropic reservoir, using a uniform line sink model.

Conversely, calculations using a uniform gene-size model (which lack this bias) will produce non-target gene p-values of a given significance strength more frequently than will actually occur in real-world calculations using real, variable-length gene data.

That means that target gene discovery yields calculated using a uniform gene-size model will slightly underestimate the actual yield that will be obtained in real-world calculations using real, variable-length gene data.

The observed relationship and interpretation of data using a uniform-stress model has revealed fundamental differences in the nature of the microstructure present in carbon fiber produced from polyethylene compared to carbon fiber produced from polyacrylonitrile (PAN) or pitch precursors.

We assumed that all models were equally probable using a uniform prior on the model space: p (M ) = (∑ i = 0 J − 2 (J − 1 i ) ) − 1 = (2 (J − 1 ) − 1 ) − 1 where i is the number of change points in the model M. If i = 0, the model M represents a constant fit to the time-course gene expression trajectory, indicating non-differential gene expression.

Significant membership to multiple populations (e.g. >5%, Senn and Pemberton (2009)) is interpreted as admixture: The model was run using a burn-in of 5 × 10 and a run of 10 Markov chain Monte Carlo steps, under the standard model of admixed ancestry (with the parameter alpha inferred from the data, using a uniform prior) and the model of correlated allele frequency (λ = 1).

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