Since the mid 1990s, microarray analysis has become one of the few tools that can analyze the entire contents of a cell regarding a specific information type.
The microarray analysis has revealed the downregulation of genes for several chlorophyll a/b binding proteins and suppression of the rice ortholog of GUN4, a critical activator of chlorophyll synthesis in Arabidopsis (Larkin et al. 2003).
Phenotype microarray analysis has demonstrated that this strain can utilize several organic acids including lactic acid, succinic acid, malic acid, citric acid and fumaric acid as sole growth substrates.
For example, microarray analysis has detected ~1300 mRNA species in EVs of the mouse mast cell line MC/9; detected mRNAs comprise 8% of total mRNA in cells of origin [21].
Previous microarray analysis has suggested remarkably similar expression pattern between the three cell lines [28].
Microarray analysis has identified breast cancer subtypes with distinct gene expression profiles [4], [5].
Similarly, microarray analysis has also failed to detect any single genes associated with invasive disease [22].
To date, the main approach in microarray analysis has been the discovery of differences between pathogenic samples.
Furthermore, microarray analysis has shown that chronic exposure to nicotine can cause alteration of gene expression in over 160 genes [9].
A microarray analysis has indicated that the gene expression pattern of the human MDA-MB-435 [4] resembles that of human melanoma cell lines [5].
Microarray analysis has been used frequently to identify groups of genes associated with various diseases, including infectious diseases [11], autoimmune diseases and cancer [12].
