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Two military and one control user sample datasets were identified from one state in the West Coast ((p_{3}), (p_{10})), South East ((p_{22}), (p_{23})), and South Central U.S. ((p_{12}), (p_{15})).
These datasets were identified from Gene Expression Omnibus (GEO) or caArray and CEL files downloaded.
To assess the method developed on transcriptomics data, datasets were identified from ArrayExpress [ 21, 23- 29] and NCBI GEO [ 30] by searching for the term 'Osteoarthritis'.
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Given the poor overlap of genes reported as being differentially expressed during drought stress in different studies (see [ 11, 12, 36]), genes regulated by drought in our datasets were identified by comparing probe intensity values from individual channels between stage 2 and stage 0 in Col-0.
By applying this pipeline to multiple poly(A -/ribo- RNA -/ribo-asets, 19 sno-lncRNAs were identifiedatasetsifferent species and/or different cell lines (Table 19.
Content or thematic areas were identified from both datasets, compared and contrasted.
Tissue-specific gene signatures were identified from three datasets: NB [ 30] and GNF [ 61], both based on Affymetrix microarrays, and GTEx [ 62].
Finally, 10338 unigenes were identified from contigs dataset.
Candidate differentially expressed miRNAs were identified from the dataset by Student's t-test analysis as described below.
A number of neutral or nearly neutral substitutions were identified from the dataset that appear to be the result of homologous mutations in a common ancestor that have subsequently been randomly assorted in modern species [ 3].
In total, 185 fusion transcripts were identified from all RNAseq datasets.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com