Sentence examples for under a null model from inspiring English sources

Furthermore, using a Monte Carlo test, a significance probability is computed in order to assess how likely any stability measure is, under a null model that specifies the absence of cluster stability.

We show that the compartments are closer than expected under a null model for their spatial point distribution, and furthermore that their spatial association varies according to cell state.

Several methods have been developed to reduce the complexity of networks through the identification of their characteristic features, which involves determining the differences between observed and expected patterns under a null model of random connections.

The null distribution can be generated by simulating under a null model of no positive selection.

Disturbed plots were significantly more 'clustered' than expected under a null model of community assembly, whereas undisturbed plots did not deviate from random expectation.

The average phylogenetic diversity expected under a null model of community assembly is reflective of the underlying phylogenetic structure of the species pool.

Sites are the number of rRNA positions followed by group I and spliceosomal introns in each conservation class and the number of observed and expected introns (in brackets [under a null model of random insertion]) is shown for each gene.

We maximized the l n L under both a null model of constant population size and a bottleneck history and calculated E [ Δ l n L ] between the two scenarios.

We compute the significance of the difference between two curves by comparing the difference in the areas under the curves against a null model estimated by a permutation test (see Methods).

The LRT statistic for an alignment block B is based on the ratio of the likelihood of the sequence alignment under two different models: 1) a null model and 2) an alternative model with acceleration in the hominin lineage that allows a faster rate of substitutions on the human and chimp branches, as described in Pollard et al. (2009).

The test is based on a null model under which, in a comparison of two alternative hypotheses, for example, H1 = ((X − Y),Z) versus H2 = ((X − Z),Y), the number of RGC_CAMs that are shared by two lineages due to chance (NXY and NXZ) is proportional to the length of the branch, the position of which differs between the compared hypotheses, that is, Y and Z, respectively, in the above example.