Microarray analysis techniques are used in interpreting the data generated from experiments on DNA, RNA, and protein microarrays, which allow researchers to investigate the expression state of a large number of genes - in many cases, an organism's entire genome - in a single experiment. Such experiments can generate very large volumes of data, allowing researchers to assess the overall state of a cell or organism. These large data amount can be difficult to analyze, especially in the absence of good gene annotation.
Read more about Microarray Analysis Techniques: Introduction, Creating Raw Data, Background Correction, Quality Control, Spot Filtering, Aggregation and Normalization, Identification of Significant Differential Expression, Pattern Recognition
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