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We analyzed a portion of the coding region of mtDNA (tRNA Leu, ND1 and tRNA Ile genes), using individuals belonging to extended families from the Azores Islands Portugall) with the main aim of providing empirical estimations of the mutation rate of the coding region of mtDNA under different assumptions, and hence to better understand the mtDNA evolutionary process.
The main aims are: a) to provide empirical estimations of the mutation rate of the coding region of mtDNA under different assumptions, and b) to better understand the mtDNA evolutionary process, including the factors that control the levels and progress of mtDNA heteroplasmy until the intraindividual fixation of new arising mutations.
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This was particularly apparent in this study: switching from μ = 0.0005 to μ = 0.00001 multiplied the estimated age by a factor of 7. To date, there is no estimation of the mutation rates for yam microsatellites but we know from previous studies that they can vary from 10-2 (human) to 10-6 (dependinga) depending on the organism and on the microsatellite pattern [ 22, 23].
The same procedure was followed for an estimation of the mutation rate in vivo, but in this case, 8 mice were inoculated intranasally with approximately 5×105 bacteria per animal from log-phase cultures of PA14 and the mutS-deficient strain.
The program uses the Markov Chain Monte Carlo algorithm to allow Bayesian estimation of the mutation age based on the following parameters: the observed genotypes (or haplotypes) in samples of unrelated normal or affected chromosomes, map distances between markers and the position of the mutation relative to the markers and the estimated population growth rate.
A cloning efficiency of 20% was considered for the estimation of the mutation rates.
Estimation of the mutation rate and the confidence interval was generated using MATLAB (MathWorks, Natick MA).
In this case, the user is warned that the estimation of the mutation rate is not reliable.
Because of this relatively low prevalence, large patient and control groups are needed to obtain a reliable estimation of the mutation frequency of SQSTM1.
The division with the minimum variance of T0 S, S') is taken as our best solution to the problem, and the corresponding K as an estimation of the mutation rate.
standard deviation; Θ_π, estimation of the mutation parameter (Theta) from the mean number of pairwise differences (Pi); RI, average raggedness index.
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