Sentence examples for mutation rate heterogeneity from inspiring English sources

Author's response: Because we use the rate of only parallel synonymous evolution as a proxy for mutation rate, heterogeneity of the rate of evolution across synonymous sites, due to heterogeneous mutation and/or selection, should not be a problem.

The history of cytochrome c research shows that the present understanding of its mutation rate heterogeneity has progressed in conjunction with study of its molecular structure and its associated pseudogenes.

Because of mutation rate heterogeneity in mtDNA there is not a consensus on the weights to be assigned to the mutated nucleotide positions.

Since BIC based model inference further indicated mutation rate heterogeneity in the concatenated MLST gene data set comprising the entire set of 29 strains as outlined above, we calculated Φw using PhiPack [38] to screen for signs of intragenic recombination in the 1092 processed sequence alignments.

Estimation of a background mutation rate can be significantly affected by mutation rate heterogeneity across different DNA contexts.

For simulated sequence with mutation rate heterogeneity and no population growth, π among sequences was estimated as 2.545 × 10−3.

Standard genome sequence analysis cannot detect all driver mutations due to difficulties in the estimation of the background mutation rate and underlying genetic heterogeneity of adaptive phenotypes [ 4, 5].

The accuracy of ancestral inference, even among relatively closely related species, has a complex dependence on branch lengths, the location of lineages within a phylogeny, rate heterogeneity among mutation classes (levels of base composition bias) and among lineages (changes in base composition).

In each model we proposed several values for each prior: a range of values for the population size, two values for the growth rate, several values for the migration rate, a range of values for the mutation rate, one value for the heterogeneity rate and four lengths of the nucleotide sequences.

Importantly, using real population genetic data to train our classifier will expose it to heterogeneity in mutation rate, recombination rate, and read depth.

Indeed, since the high mutation rate results in enormous tumor heterogeneity, most likely already at the beginning of a therapy, the mutations conferring resistance to the chosen drug will be present in a subset of tumor cells.