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At least 200 white blood cells in each sample were classified.
Net normalized signal values from each sample were classified into four grades for better analysis.
Based on the mapping results, the alignment reads and unique hit reads in each sample were classified by SOAP2.
Based on known annotation information of protein-coding genes, ncRNAs, pseudogenes, and lincRNAs, transcripts in each sample were classified into sets of protein-coding genes, lincRNAs, known ncRNAs, pseudogenes, and unannotated transcripts.
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The leave-one-out error rate is the average error rate when each sample is classified with a k-NN classifier that has been trained with the remaining n-1 samples, thereby yielding a single performance measure.
For each aCGH R-segment, each sample was classified as being copy number normal, gained or lost based on log2 ratio thresholds of +/−0.15.
Given that mean refers to the mean value of one feature in all samples, and std is the standard deviation, the features of each sample
Every contig from each sample was classified into four groups (contigs without genes, contigs with sample-specific genes, contigs with only one gene, and contigs with multiple genes).
Each sample was classified by whether there was a prominent superficial nesting pattern on routine haematoxylin and eosin examination (group 1, 31 samples), or only a diffuse dermal infiltration without nesting (group 2, 35 samples).
Each sample was classified as Active or Inactive using the Pearson correlation coefficient for median-centered expression of that sample versus the vector of up (1) and down (-1) genes in the Active patients from the 72 patient set.
All isolates obtained from each plant sample were classified according to their morphological appearance into morphotypes.
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