Sentence examples for microarray clusters to from inspiring English sources

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.

This confirms our findings in Ingenuity Pathway Analysis of the microarray clusters.

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.

Trp53, Ctnnb1, Bmp7, Bmp10, Ccnd2, Apaf1, and Brca1 additionally identified the Ingenuity canonical pathway for molecular mechanisms of cancer, again confirming our findings from Ingenuity Pathway Analysis of the microarray clusters.

To date, a few clustering algorithms designed to exploit the digital data structure have been developed for SAGE data analysis, and shown to perform favorably compared to conventional microarray clustering algorithms [12].

Therefore we decided to rerun the microarray clustering analysis excluding this animal in order to verify its influence on the final results.

Surprisingly, microarray clustering showed F1 male profile as closest to F1 female and F0 male profile closest to F2 male.

The microarray cluster enrichment analysis in particular revealed a large over-representation of genes known to be controlled by DAF-16 (Additional file 2) [ 25].

Lauretta Grasso kindly made microarray cluster analysis data available.

The performance of the proposed multiobjective clustering method has been compared with that of several other microarray clustering algorithms for three publicly available benchmark cancer datasets.

All microarray cluster analyses were displayed using Java Treeview version 1.1.3.