Sentence examples for modeling such traits from inspiring English sources
Technologies for high-dimensional phenotyping are becoming widely available in evolutionary biology and ecology so methods for modeling such traits are needed.
Traits with a constant CV, given the explanatory variables, are naturally modeled using a gamma distribution (M ccullagh and N elder 1989), and the DGLM method can be adapted to model such traits by setting the dispersion to CV (see File S1).
Most immediately, these data will provide a foundation for modeling complex traits such as metabolic regulation, a dynamic phenotype that varies between these populations (Greenberg et al. 2010, 2011; Scheitz et al. 2013), and which is amendable to increasingly numerous and sensitive "omic" assays.
Although one can certainly raise caveats for some of these previous studies, and a simple genetic basis can be questioned in some cases, it is quite clear that color polymorphisms in lizards are often heritable, making such traits useful model systems in studies of the relative role of genetic drift vs. selection.
Such traits have been successfully modeled in game theory as conditional strategies, and in quantitative genetics as threshold traits.
The test subjects were asked to assign to each model such qualities as power or friendliness and to chart such traits as happy, sad, angry or surprised.
Worse, such traits could appear highly adaptive on evolutionary models.
We maintain that there must be uniquely human traits for which there are no animal models and it remains possible that mental time travel depends on several such traits.
Here, we warn that there must also be uniquely human traits for which there can be no such animal models and suggest that human mental time travel may be based on several such traits.
Could such traits be genetically correlated to wing pattern traits?
Understanding how such traits link to large scale features of the environment may improve models that account for variation in strength of consumer effects across landscapes.
