Your English writing platform
Discover LudwigSuggestions(5)
Exact(20)
We found no significant enrichment for this subset of probes in any set of our GR or ER hits, when using either the entire genome or the subset of ∼2,000 most variable probes as the background set.
Unsupervised clustering on approximately 3,500 of the most variable probes resulted in two distinct clusters.
Data were standardized across samples and within platform and merged, and the top 1000 most variable probes selected for analysis.
For computational reasons, only the 5,000 most variable probes (across all samples) were used for the network construction.
The microarray dataset was filtered before clustering in order to select the 2,000 most variable probes.
For unsupervised hierarchical clustering, the top 8,000 most variable probes (by standard deviation) were utilized with average linkage and Pearson correlation algorithms across the dataset.
Similar(38)
The overlap between the most variable probe sets in FF tissue and the most variable probe sets in FFPE tissue (FF: 5000/FFPE: 17 853) consisted of 4620 matching probe sets.
We then selected the most variable probe sets per gene (n=17 583), and of these, the 5000 most variable probe sets on FFPE expression profiles.
Similar to [ 4, 60] we chose the most variable probe set for each gene as a representative in this article.
We extracted the most variable probe for all covered UC DMRs (3,361 probes) and investigated the average methylation state in tumors versus adjacent normal tissue (21 samples).
Selecting the most variable probe set on exon arrays does not always identify those with highest correlation to expression on HU133plus2.0 arrays.
More suggestions(15)
most extreme probes
most powerful probes
most reliable probes
most sensitive probes
most promising probes
most penetrating probes
most specific probes
most such probes
most convenient probes
most variable phenotypes
most similar probes
most variable parameters
most complex probes
most previous probes
most popular probes
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com