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We can obtain the distribution F ij from the background mutation model described in the Section 2.2.
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By examining the overall number of nucleotide substitutions involved in the stepwise mutation model previously described, we found that from the six nucleotide changes involved in the pathway leading to mammalian H2A.Z-2, two reach maximum levels of probability as estimated in Table 4.
In contrast, Fisher's geometric model described above assumes that each mutation potentially affects all traits, and hence the more traits an organism has (the higher its complexity), the higher is the potential dimensionality of a mutation.
The mouse model described here suggests that TET2 mutations play a major role in the development of T-cell lymphoma with Tfh-like features in humans.
The effects of some conserved amino acid mutations do not fit the proposed ATP binding site model (described above), and can vary markedly between different P2X receptor subunits.
We developed a mathematical model describing the accumulation of advantageous, deleterious and neutral mutations by clones within a growing tumour.
The clonal interference model describes the dynamics of evolution when different beneficial mutations occur in multiple individuals before one of them can rise to fixation.
The non-stationary solutions of the model describe efficient adaptive pathways for the molecular evolution of regulatory networks by point mutations.
It is calculated from the background mutation model which will be described in the Section 2.2.
Many population genetics inference methods for microsatellite data require the adoption of a mutation model such as those described above.
We use the background mutation model that will be described in Section 2.3 to get an empirical Bayes estimate of b jg.
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