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Next, we tested the predictive power of divergence in three-way classification on a dataset balanced to have equal class frequency (Table 10).
We further tested the prediction power of divergence features when combined with classical features computed on a 20 residue N-terminal instead of 40 (which might be too long for the SP class).
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Against a backdrop of hundreds of comparative transcriptomic studies in many species, the power of expression divergence as a predictor of trait variation has remained largely invalidated.
By dissecting the iron scarcity specialist behavior of Malaysian yeast, our work highlights the power of expression divergence as a signpost for biologically and evolutionarily relevant variation at the organismal level.
The initial power law phase of divergence lasts longer in this case.
To explore how the amount of data affects statistical power of inference of divergence dates, we used estimates of species neutral evolution rate based on third codon substitutions of cytochrome b for 131 carnivore species [ 35].
Figure 2 compares the power of the Bayesian divergence point method with two other statistical tests for heterotachy given pre-defined subgroups.
We consider Schrödinger semigroups e−tH, H = −Δ + V on Rn with V ~ −c¦x¦−2, as ¦x¦ → ∞, 0 < c < [(12)(n − 2)]2, with H ⩾ 0. We determine the exact power law divergence of ∥e−tH∥p, p and of some ∥e−tH∥q, p as maps from Lp to Lq.
This observation is consistent with results of a simulation study by [ 27], who revealed that the accuracy remained high and that increasing the number of lineages was the best way to increase statistical power, even at high levels of divergence.
Since Branch models make the unrealistic assumption of among-site homogeneity, they often lack power to detect subtle patterns of divergence across phylogenies, and we conducted post-hoc Branch model analysis simply to help demonstrate our Clade model partitioning schemes (described below).
The discriminatory power of Cops-1 sequence divergence was compared to genotyping using a standard C. parvum marker (Gp60) and a multi-locus subtyping approach (Bouzid et al. 2010a).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com