The challenges in gene expression research can be compared to astronomers investigating the myriad of stellar constellations. The StellARray™ Gene Expression qPCR arrays offer life scientists a revolutionary qPCR system that helps you to focus on the gene “constellations” relevant for your individual research area and frees your gene expression profiling from unwanted bias. This unique system makes gene-by-gene expression analysis, microarray data validation, biomarker discovery and siRNA knockdown verification simple, fast and reliable.
Currently, the most common approach to gene expression analysis is to use housekeeping genes as normalizer genes, assuming that the expressionlevel of the housekeeping gene does not change in the context of the experiment. However, housekeeping gene expression often changes when tissues or cells in different states are compared. Any small variation in the housekeeping gene expression compromises the analysis of the complete qPCR data set.
The selection of the genes on each StellARray™ qPCR Array involves extensive “sieving” of data using the advanced capabilities of the GeneSieve™ Bioinformatics System. The GeneSieve™ System is composed of several modules that work together to assemble ‘constellations’ of genesassociated with specific biological pathways and processes. StellARray™qPCR Arrays and GPR Analysis Software are designed to be used for expression profiling, as well as the determination of gene copy number. By applying genomic DNA as template, the StellARray™ System easily and accurately determines the number of copies of the gene(s) responsible for the expression levels observed.
The Global Pattern Recognition™ Analysis Tool provides a means to answerthe fundamental question of how to analyze data and determine realchanges in gene expression. Through an innovative algorithm developed by Bar Harbor BioTechnology, Inc., scientists are able to detect biologically significant expression changes, in some cases less than 2-fold changes, that would normally be missed. In addition, this algorithm eliminates the need to run housekeeping gene "controls" that could generate false data.
I have tested it on the CDX4. I needed the results quickly for an exercise on the gene. I wanted proof that CDX4 dysregulates the Hoxgene expression and generates acute myeloid leukemia alone and in cooperation with Meis1a in a murine model. I was worried that the results would be terrible, but they were better even than my teacher's. The data show more detail and my tutor now also uses also the system.
