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However, it is clear that the dramatic changes in gene expression in the predominant FFUF and FFDF microarray clusters were replicated by the qRT-PCR analysis for many of the tested genes.
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For microarrays, transcript clusters were considered expressed if at least one probeset targeting the same transcript cluster had a detection p-value < 0.05 in at least 5 of the 32 samples.
Because of the notable link between arsenic toxicity and cancer formation in other organ systems, genes which have been previously linked with cancer and which may be important in arsenic toxicity were chosen from the 10 k microarray clusters to be further confirmed via real-time PCR.
By integrating the data from both microarrays, nine co-expression WRKY gene clusters were identified (see Figures 2 and 3), some of them restricted to specific experimental conditions, while others found in a larger set of them.
In the data collection and preprocessing step, gene expression clusters were identified from a microarray dataset and cluster expression levels were converted to discrete values.
Microarray sequence features were mapped to NCBI Unigene clusters [ 28], and redundant clusters were condensed by averaging expression measurements.
All microarray cluster analyses were displayed using Java Treeview version 1.1.3.
All microarray cluster analyses were displayed by using Java Treeview version 1.1.3.
Three gene clusters were selected for each species by hierarchical clustering [ 64] from the microarray databases.
(Full annotation of each microarray platform to HTR clusters is available as Additional file 5) The microarray features of all four platforms provided a total coverage of 26,103 HTRs, and 6,342 out of 6,553 (96.8%) of the differentially expressed transcripts obtained by MPSS were represented on one or more of these genome-wide platforms.
For example, in one study involving microarray clustering, higher resolution clusters are in general subsets of lower resolution clusters [ 30].
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