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Raw PM intensities from each array were subjected to local background correction using MAS5 method, log2-transformed and median-centered.
The same samples, FF1 and FFPE9 analyzed by the 96.96 dynamic array were subjected to gene expression profiling using the Affymetrix miRNA arrays.
The seventy five SND2∩Ko genes represented on the ATH1 22k array were subjected to hierarchical clustering across the Genevestigator V3 Arabidopsis anatomy database [ 39] as before to analyze their tissue specificity.
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Following normalization each probe within each array was subjected to a smoothing procedure, whereby the probe's M values were replaced with the median value of all probe M values within a 600 bp window is at least 4 probes were present in the window and NA if less than 4 probes were present in the window.
The array was subjected to normal/normal hybridisation in order to eliminate clones that deviated from 0 by greater than +0.2 or less than −0.2.
The sequence of every transcript on the array was subjected to KEGG analysis to generate an overall picture of the relative abundance of genes in the KEGG pathways.
This is probably an indication of the relative closeness of the dye-labels in the light frequency spectrum, leading for example to fluorescence of the Cy3 channel when the array is subjected with the laser frequency corresponding to Alexa594.
Expression readouts of the miRNA arrays were subjected to paired, volcano-plot analysis to arrive at differences of means for each miRNA in 10-87 LP cells compared with 10-87 HP cells and 10-87 T cells, and 10-87 HP cells compared with 10-87 T cells.
Arrays were subjected to a Loess transformation and the CyberT-statistics were calculated.
All 36 arrays were subjected to data pre-processing, e.g. filtering of low intensity signals, background correction, within array normalization and between array normalization.
Data from the arrays were subjected to "normexp" background subtraction, followed by LOESS within-array normalization and "Gquantile" between-array normalization.
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