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As a result, we simulated a dataset of a molecular complex with multiple conformations that are fixed in ice with random orientations.
We then simulated a dataset based on the initial population and the final population allele frequencies, and the number of individuals sampled in our real dataset in the two populations.
We simulated a dataset with 400 genes and 50 samples.
We simulated a dataset of 60 gametophores in which branching occurs stochastically with a probability of 5% to obtain a similar number of branches to WT.
using observations of GSA results of real data, we simulated a dataset of 400 pairwise tests by 400 gene sets in which we placed seven modules (M1 M7; Fig. 1).
Since the sequencing depth of the 454 dataset is not very high (2.86×) and contains a eukaryote organism, we also simulated a dataset with higher depth (9×) that included only the prokaryotic species from the dataset.
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We also simulated a realistic dataset (ER) from ∼97 000 ENSEMBL transcripts.
Initially, we simulate a sequencing dataset with the same length distribution and nucleotide composition as the input dataset.
To compare speed and accuracy of prediction of emBayesR with that from BayesR, we used both a simulated dataset and a real dataset on 630 K SNPs for dairy cattle.
For simple two-group comparison, we show that our method outperforms developed methods in accurately detecting the complete DM region on a simulated dataset and an Arabidopsis dataset.
The method was tested on a simulated dataset, and a beef cattle dataset using a model that included principal components from a genomic correlation matrix derived from the allele frequencies estimated from the pooled samples.
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