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When applied to a well-known yeast microarray dataset, the BBC procedure discovered many biologically significant clusters, from which significant enrichments of gene functions, associated experimental conditions, and related TFBS enrichment were found.
If a statistically significant enrichment of expressed FBX genes was observed in a microarray dataset, the biological functions tested by the microarray was retrieved.
Independently for each microarray dataset, the mean VMR and CV for the unique, segmental duplicated and tandem duplicated genes were then compared to the appropriate random sampling distribution to test for a significant difference from the genomic mean.
In our DNA microarray dataset, the IFNB1 (IFN-β) gene is upregulated 80%.
For the microarray dataset, the gene must have log2-transformed expression value ≥ 7.65 in at least one condition.
Using a large-scale gene expression microarray dataset, the ARACNe algorithm was applied to both tissue types independently.
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For both microarray datasets, the gene expressions were extracted from the.
Thus, for the studied microarray datasets, the discretization of gene expression values is an essential step.
PTHLH expression profiles of renal tumor in the published DNA microarray datasets (the GEO datasets, GSE11151 and GSE15641).
By rematching and reannotation of the existing microarray datasets, the results obtained from the microarray experiments could be used for lncRNA analysis concurrently.
Therefore, we referred to the PTHLH expression profiles of renal tumor in the previously published DNA microarray datasets (the GEO datasets, GSE11151, and GSE15641; Table S1).
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