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In this study we report correlations between standardised measures of intelligence and mutational class, mutation size, mutation location and the involvement of dystrophin isoforms.
Here we report correlations between standardised measures of intelligence and mutational class, mutation size, mutation location and the cumulative loss of dystrophin isoforms, focusing in particular on the risk of cognitive disability for mutations that involve the dystrophin isoform Dp140.
The parameter a mutates at a rate of 0.075, and the mutation size is drawn from a Gaussian distribution (μ = 0, σ = 0.15).
An intermediate maximum mutation size μ leads to a maximal number of clusters.
The model presented here illustrates that mutation size can affect the formation of clusters of organisms in a continuous morphospace.
We investigate the clustering of organisms, where clusters are defined as reproductively isolated groups and serve as an analogue of species, as a function of maximum mutation size.
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For example, the cases where mutation sizes are normally distributed (Figures 5 and 6) exhibit transitions in the parameters of interest for significantly higher values of μ than the cases where mutation sizes are uniformly distributed (Figures 3 and 4).
The model studied here is remarkably robust across various modifications, including changes in how the landscape varies (gradual shift vs. feedback) and in the distribution of mutation sizes (uniform vs. normal).
Stampy and Omixon eanbled good downstream detectability across the range of mutation sizes in the panel.
Mutation sizes are highly variable, ranging from point mutations to deletions covering tens of kilobases to over nine megabases.
Traditionally, Southern blot analysis has been considered the most accurate method to size the full mutation and to determine the methylation status of the expanded alleles for all mutation sizes.
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