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Implementation of these models and computation of some criteria for model comparison were illustrated using two simulated datasets.
The performance of the proposed method was evaluated using two simulated datasets.
The performance of this method is then evaluated using two simulated datasets.
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The model was evaluated using three simulated datasets consisting of a timeseries of progesterone values centred on each of the three reproductive statuses and including relevant additional information.
We used three simulated datasets (one with the problem of many extremely low-abundance species and one with the problem of low-abundance species without too many extremely low-abundance species and one with both problems) and a real dataset [from (Qin et al., 2010)] to evaluate the tools.
We tested the assignment performance of different methods using three simulated short read datasets, simulated 16S rRNA data, three simulated metagenome contig datasets and using assembled cow rumen metagenome contigs.
Genotypes for two kinds of pedigrees were created with generation 0, and were used to produce two simulated datasets i.e. Data I and Data II.
To assess the sensitivity of our method to those truncated L1 elements (L1 Homo sapiens, L1HS), we generated two simulated datasets using the same strategy as the Alu simulations with 5′ truncated L1 elements (See Methods); heterozygous 106 bp at 10X and 20X sequence coverage.
We illustrate the use of the package with two simulated datasets, one under the true model and one with different parameter values, to show how npde can be used to evaluate models.
Fourteen datasets are used to compare the five methods for periodicity detection, comprising two simulated datasets and twelve DNA microarray datasets taken from an online database.
The two simulated datasets were generated at random from the E. coli K-12 genome using 36-bp reads with 100× coverage depth and 1% mismatch errors, and with 100-bp reads with 200× coverage depth and 1% mismatch errors.
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