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We review the evolution of microarray platforms used for such studies in order to meet the criteria of complex tissue engineering biological environments.
Merging did not deteriorate performance on average despite (a) The diversity of microarray platforms used.
The reason for this difference in the two data sets is likely due to the difference in microarray platforms used in these studies.
Gene lists: We analyzed the list of human or mouse genes from the UCSC GoldenPath database "known gene" table intersected with the microarray platforms used (independently in human and mouse analysis).
Details of the numbers and anatomical subsites of procured tumor samples, microarray platforms used, analytical methods conducted, original identifiers reported, information regarding fold changes, and the availability of datasets were provided in Table S1.
The set of pathways obtained from the MSigDB covers more than 5,000 distinct genes, where 3,271 of them can be found in both microarray platforms used by the two breast cancer gene expression studies in [10], [11].
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Because microarray platforms use their own element IDs rather than common gene IDs, two search tools were developed to determine the relationship between microarray elements and rice genes.
But data integration prior to analysis potentially faces problems related to reproducibility as different microarray platforms use different probes for the same genes and return expression values on different numerical scales.
The results were compared to standard qPCR and hybridization-based microarray platforms using the same samples.
For example, different microarray platforms use different probe design and labeling and have different dynamic ranges.
In addition to gene set analysis, canonical pathway analysis was performed using 179 genes identified in more than three microarray platforms using SAM analysis.
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