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We investigated whether the higher AUC of our weather models was due to the greater number of variables than in our climate models by running our weather models for each species with only four weather variables.
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These initial rates were estimated with BEAST under the UCLN model by running two MCMC samplers independently.
However, there is intracellular variability in the expression of UCH-L1 in the experiments and so we accounted for this in the model by running sets of simulations with different levels of UCH-L1.
We checked the sensitivity of the data to the mutational model by running additional trials using multiple SMM/IAM combinations.
We thus derived a model by running our approach with λ = 0.004 and all the 1,752 subjects in the data.
For compound 3, the disorder was modeled by running the Hirshfeld surface analysis for both possible orientations of the propyl esters.
We assessed if the morphological variables explained a significant part of the variance in the model by running an ANOVA on the pGLS output.
Finally, we explored the robustness of the imputation model by running the above-mentioned analysis on 20 and 150 imputed data sets.
We decided on the GTR + Γ model by running PartitionFinder on a subset of loci, but not all, to reduce computational burden.
To assess the added value of each of the different measures we first investigated the benefit of including multiple measures of physical capability in the same model by running a sex adjusted model with all three measures included.
Using our implementation of protein age, that is more congruent with the bioinformatic data analysis, we systematically study the DD model by running it under many different parameter conditions.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com