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Find out how the StellARray™ Gene Expression System overcomes fundamental challenges in gene expression research.
Gene Expression Challenge #1: From the many thousands of genes existing, what are the genes to focus on in a specific research theme? How to get the assays running to analyze all of them?
More than 150 pathway or disease area specific StellARray™ qPCR Arrays in 96- and 384-well plate formats are available off-the-shelf to cover a broad range of research areas:
Allergy - Angiogenesis - Adipositas - Blood disease - Cancer - Cardiovascular disease - CNS disorder - Developmental biology - Immune disorder - Immunology - Infectious disease - Mental disorder - Metabolism - Signal transduction - Stem Cells - Toxicology - Wound healing
Find the ideal StellARray™ qPCR Array for your research area or customize your individual StellARray™ qPCR Array with the gene list of your preference.
Gene Expression Challenge #2: What normalization should be done in order to determine REAL gene expression changes?
Currently, the most common approach is to use housekeeping gene as normalizer genes, assuming that the level of expression 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 state are compared (Bustin 2000; Schmittgen et al. 2000; Goidin et al. 2001; Hamalainen et al. 2001). Any small variation in the housekeeping gene expression compromises the analysis of the complete real-time PCR data set (Fig 1).
StellARray™ Gene Expression System lets your experiment define the best normalizer gene:
- The StellARray™ System does not work with housekeeping genes as predefined normalizers
- Normalization is based on lowest variance within gene constellations of a qPCR array
- The complimentary Global Pattern Recognition™ Analysis Software automatically determines and applies the best normalizers within seconds
| Which data would you trust? |
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Fig 1 Using the conventional ΔΔCT method for analysis of qPCR data, the same experimental qPCR data set was
analyzed four times by normalization to each 18S, GAPDH, GPI or HPRT as traditional housekeeping genes. Depending on the
selection of the housekeeping gene for normalization, very different gene expression profiles were obtained. The
StellARray™ System does not work with predefined normalizers, or housekeeping genes. By using the
StellARray™ System, the experiment defines the best set of genes for normalization to ensure highest
accuracy of analysis.
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Learn more about Global Pattern Recognition™ data analysis.
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