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Gene expression profile analyses revealed that the contigs may be classified into 13 different clusters of gene expression patterns.
Newer technologies offer the possibility of evaluating thousands of genes and identifying clusters of gene expression associated with significantly different risks of relapse and patterns of sensitivity/resistance to specific drugs.
Figure S4 shows clusters of gene expression analyzed using DAVID.
In other words, we are seeking clusters of gene expression dysregulation events in the network.
Four clusters of gene expression are shown in Figure 2 to illustrate profiles of expression that are dependent or independent of developmental age and/or the nutritional environment.
By average linkage of hierarchical cluster analysis, 12 clusters of gene expression profiles could be defined using Bb oral infection microarray data (Fig. 3).
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Recent research has found clusters of genes that can be used to identify broad racial categories like white, African-American, Hispanic or East Asian.
After statistical and hierarchical cluster analyses, we determined five clusters of genes differentially affected by the four inhibitors used.
Moreover, the clusters of genes for biosynthesis regulating the metabolite profiling need to be investigated in future.
Clusters of genes with common function were assessed with GSEA.
Two of them are clusters of genes enriched for developmental processes.
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