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Overall, the microarray experiments generated high quality data without significant dye-dependent effects and skewness of ratio distribution.
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Microarray experiments generate vast quantities of raw gene expression data, therefore good experimental design and statistical analysis is required for the extraction of accurate and useful information regarding the expression of genes.
However, a comparative analysis of the above mentioned studies revealed rather weak overlap of catalogued gene expression profiles [7], which is mostly a consequence of microarray experiments generating large sets of data that are not directly interpretable.
Microarray experiments generate an amount of data that cannot be handled by simple sorting in spreadsheets or plotting on graphs.
Microarray experiments generate differential molecular signatures under physiological and biochemical perturbations that reflect genetic regulatory mechanisms [ 16].
Microarrays have been an exciting research tool for two decades, but what I find so compelling about microarray experiments in the educational context is the broad range of topics and mathematical complexity that microarray experiments generate.
Microarray experiments generate large amounts of information whose analysis and interpretation are nontrivial 4. Traditional statistical approaches are challenged by large variances, incommensurability, nonnormality, and the small number or replicates frequently present in these experiments.
Compared to traditional clinical outcome measurements where a single biochemical measurement or histopathological score is interpreted, gene expression signatures resulting from microarray experiments generate a molecular fingerprint consisting of multiple biomarkers which cannot otherwise be interpreted in isolation.
In the first set of microarray experiments, we generated gene expression data from ten lingual epithelium (LE) samples and ten taste bud (TB) samples - six from FG papilla and four from CV papilla.
GHW performed microarray experiments and generated array data.
EC, CR and NA performed the microarray experiments and generated the call rate data.
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