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In the 2004 sample, we employed lasso regression [27] with five-fold cross-validation [28](p.
To test the normality of the distribution of migration speed values for neutrophils in the same sample we employed the Shapiro-Wilk test, indicating if the data is likely to be derived from a normally distributed population (p>0.05).
After performing microarray experiments in a control sample, we employed RNA sequencing to profile the whole transcriptome.
To determine whether there was any significant association between SNPs and ND measures in the EA or AA sample, we employed the PBAT program under different genetic models (Table 3).
To normalize for variation in the distribution of tags between libraries as well as to compensate for variable numbers of tags generated for each sample, we employed the program edgeR (http://bioconductor.org/packages/2.5/bioc/html/edgeR.html; Robinson and Smyth 2007, 2008).
To ensure the representativeness of this sample, we employed a diverse range of purposive, theoretical and strategic sampling methods [ 29, 30] to recruit participants who were representative of a broad range of socio-cultural, demographic, geographic and weight groups within the obesity range, allowing us to explore the findings in the context of socio-cultural risk communication literature.
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In case two samples share the same dissimilarity from a query sample, we employ the modification suggested in McSherry and Najork (2008) to break ties.
To obtain the diffraction patterns of the HPT treated samples, we employed fast Fourier transformation (FFT) to filter the noise from the lattice image, and then performed inverse (IFFT) characterization of the targeted area.
To assess if this deletion occurred in our fibroblast samples, we employed the same PCR strategy used for detecting mtMinArc, targeting a region of the mitochondrial NADH Ubiquinone Oxidoreductase Core Subunit 4 (MTND4) gene in mtMajArc20.
In order to quantitatively analyze the difference between samples, we employed the semiclassical Drude [34] model to estimate the mobility of samples μ = (enρ)− 1. Figure 7 Electrical properties of the graphene samples.
Since CD4 counts and information on viral load were unavailable for the early samples, we employed computational approaches to infer diversity changes and to detect positive selection acting on the env gene.
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