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One important analysis task of microarray data concerns the simultaneous identification of groups of genes that show similar expression patterns across specific groups of experimental conditions (samples) [ 1].
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Our analysis, covering the major subtypes of thyroid tissue, may be expected to enhance microarray data concerning thyroid tumors and lead to the definition of more reliable tissue-specific markers for thyroid lesions.
Although the transcriptional repertoire of Plasmodium sporozoites has been investigated in several laboratories using different techniques, including cDNA libraries, SSH, microarrays and proteomics, only the microarray data has provided information concerning the level of gene expression [ 9].
microarray data reproduced, but some concerns remain.
However, in the context of microarray data analysis, multiple testing concerns are forefront.
W. E. Johnson provided important advice concerning microarray data analysis.
Concerning the microarray data for the virB expression, RNA was reverse transcribed, labeled and hybridized by NimbleGen™ Systems, Inc using the catalogue design for B. melitensis 16M chromosomes I (NC_003317) and II (NC_003318) with 20 probes per gene (10 perfect matches and 10 mismatches).
Database usage is a major concern in microarray data analysis.
As far as the theory of type 3 diabetes is concerned, our microarray data revealed a couple of genes which might provide a link between diabetes and neurodegeneration.
From microarray data some information is available concerning the Fe-deficient-dependent expression of genes related to N metabolism in Arabidopsis[ 12- 14].
For the annotated list of the 30 most highly expressed miRNAs, and lists of the up- and down-regulated miRNAs see Additional file 2 and 3. When dealing with microarray data there is always a concern that technical biases, such as variability in hybridization efficiencies and other chip artifacts, may influence the results.
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