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In all the previous studies, mapper performance was evaluated using large eukaryotic genomes (mainly the human genome) and, for the most part, short Illumina or Illumina-like reads data were used, except in [ 4, 6] where 454 datasets were evaluated with a reduced number of mappers and metrics.
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Concordance of the EF-1a gene datasets was evaluated with the partition-homogeneity test implemented with MEGA (Tamura et al. 2011), using 1 000 random repartitions.
Separately for each microsatellite, levels of variability among the 84 chimpanzee individuals and among the 5,435 human individuals in the MS5519 subset [ 66] of the genotype dataset were evaluated with He calculated using a sample size-corrected estimator [ 130], considering in the calculation only those individuals with non-missing genotypes.
Performances for all algorithms with different datasets were evaluated using two worker nodes.
Results of the docking for nine DUD datasets were evaluated using AuPosSOM clustering followed by scoring with the scoring function developed in this study.
The accuracies of these gridded datasets are evaluated by comparing them with the coordinates of the LLRR and ALSEP sites.
Reflecting analysis of a large dataset, statistical models for the change scores were evaluated with the margins function in STATA in order to provide predicted values (including 99% confidence intervals (CIs)) separately for each of the head-size and bearing categories.
Greenness trends for KRAs versus non-KRAs were evaluated with a 22-year dataset of Normalized Difference Vegetation Index (NDVI).
Best models on training dataset were evaluated on validation dataset.
Thus, at 220 of the 221 microsatellites whose chimpanzee ePCR fragments met our criteria for retention, the similarity of their chimpanzee and human PCR fragment length ranges in the genotype dataset was evaluated together with the location of their chimpanzee and previously reported human [ 74] ePCR fragment lengths within these ranges.
To provide further validation of the data, and deal with those datasets which consistency cannot be evaluated with a carbon balance, a possibilistic MFA consistency test was also applied.
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