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* ** Clustering of gene expression profiles used Gene Cluster 3.0, and the parameters used are the following: after removing genes that had good data in less than 80% of specimens examined, data were adjusted by gene centering only (no array centering), and the hierarchical clustering used uncentered correlation as the similarity metric and average linkage as the clustering method.
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e, The average number of genes that are different between two accessions in which all combinations of the 453 accessions were considered, and the proportions were calculated as the number of such differentiating genes adjusted by the gene numbers held in common by the two genome types.
Analyses were adjusted by gender.
The background for the test was appropriately adjusted by excluding those genes found to be specific for C. albicans without C. dubliniensis orthologs.
First, the HG-U133A RMA expression values were adjusted by adding a gene-wise constant defined as the difference between the mean of the test set samples and the mean of the training set samples, separately for each gene.
To this end, we averaged the medians of the SNP distributions for each alignment (i.e., the number of SNPs/alignment length of each draft genome with respect to CFN42 or CIAT652) and generated average confidence interval (obtained and adjusted by distribution of genes size medians) using Predictive Analytics Software PASW Statistics 18 (SPSS Inc., Chicago, IL).
Moreover, the codon bias of the PparoA1 gene in tobacco was further adjusted by synthesizing a PparoA1optimized gene.
Then, each animal's contribution to the next gene pool was adjusted by its fitness, the next gene pool is constructed, and the next generation is drawn.
The multivariate logistic regression was performed for acquiring odds ratios of 8 genes expression of each of the eight genes adjusted by demographics in the four different groups.
The p-values were computed based on the chi-square statistic adjusted by the FDR method; genes with adjusted P values < 0.05 were treated as candidates for positive selection.
Gene expression levels were measured through short reads mapping in RPKM [21] adjusted by a normalization factor [36].
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