Analysis of a total of 3,651 published microarray datasets identified probes for AKR1C3 in 2,373 of them.
With the rapid increase in the size of microarray datasets, identifying functionally related genes from large and diverse microarray gene expression datasets is a key challenge.
Although a perfect or the best solution to it is yet to be found, we have demonstrated that the ISML pipeline can reduce the dimensionality of microarray datasets, identify and rank classifier genes, generate a small set of classifier genes, produce an SVM classification model with high accuracy, and select a small group of biomarker candidate genes for biological validation.
Michelhaugh SK reanalyzed the existing Affymetrix microarray dataset and identified the 5 lncRNAs dysregulated in the heroin abusers [ 10].
On the mesothelioma microarray dataset, we identified five of the 6 amplified regions detected by Christensen and colleagues [ 12] applying the CGHcall package and four using the DNAcopy package.
Of genes expressed in the microarray dataset, we identified 1080 as putative transcriptional regulators using the Gene Ontology by selecting genes annotated by the following GO identifiers: GO 0003700, GO 0006350 and GO 0006351.
Data integration and various bioinformatics approaches may substantially facilitate unmasking of a cryptic microarray dataset to identify targets and to dissect underlying mechanisms.
In this work, an inference model was constructed from a diurnal cycle microarray dataset to identify candidate transcriptional regulators of plant starch metabolism.
Using our proposed meta-analysis method on the two microarray datasets, we identified 330 probe sets representing 309 genes that were significantly relevant to CAN.
Through comparative analysis of a number of microarray datasets we identified a set of genes commonly regulated by FOXO proteins and PI3K PKB/Akt, which includes CTDSP2 (C-terminal domain small phosphatase 2).
