Sentence examples for model without selection from inspiring English sources

To assess the significance of selective sweep signals, we generated a null model without selection but taking into account the known demographic history of rat strains sequenced (Ben-Ishay et al., 1972; Bianchi et al., 1974; Dupont et al., 1973; Goto et al., 1975; Jackson et al., 1981; Jong, 1984; Kuijpers and Gruys, 1984; Lindsey, 1979; Okamoto and Aoki, 1963; Okamoto et al., 1974 ).

The identification of PASS regions that were considerably longer than those observed under the null model without selection provides evidence that PASS regions are enriched for positively selected haplotype blocks.

The network model without selection is implemented, for instance, in the neuron diagrams popularized by Lewis.

The network model without selection is also implemented in the directed acyclic graphs used in causal modeling to partially visualize the models (Spirtes, Glymour, and Scheines 1993; Pearl 2000).

Based on the results of Table 6, it is noticed that the interest variable (exter) of the model without selection has a positive coefficient and is statistically significant at 1 %, confirming the hypothesis that outsourcing services is positively correlated to innovation.

In this study, we compared reaction norm and factor analytic models with the multivariate model without selection bias correction.

Previous authors [24], [25] have shown that the variance in immigration rates influences expected allele frequencies in models without selection.

Second, random site models analysis proved the existence of historical selection based on the maximum likelihood method, which revealed that, for MHC genes, the models including selection (M2a, M3, and M8) match MHC alleles better than models without selection (Table 4,and 5).

If a higher likelihood score was obtained for a model incorporating positive selection than a null model without positive selection, this constitutes evidence for positive selection.

The tree used in PAML analysis was first obtained after running M0 in PAML (model = 0 and NS sites = 0. The CODEML program of PAML assigns a likelihood score to models for selection. A likelihood score for a model incorporating positive selection (M2 or M8) that is higher than that for a null model without positive selection (M1 or M7) is evidence for positive selection.

H0 is the null branch-site codon model, without positive selection; H1 is the alternative model that allows for positive selection at sites in the foreground branches.