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Microarray technique generates a large number of information, both laboratory data and image and data files.
The rapidly developed microarray technique generates a huge amount of large-scale gene expression profiles.
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The technique generates a similar anticipatory vibrancy.
Similarly, at the transcription level, microarray techniques have generated large amounts of data enabling the construction of transcription networks for specific biological pathways under any given biological condition of interest (Curtis et al., 2005).
Microarray technique is a useful tool to identify functional gene candidates.
We used microarray technique for this purpose.
This DNA microarray technique improved detection of fragmented RNA compared with conventional techniques.
Given the inherent differences of the microarray techniques, heterogeneity of the sample populations, and low comparability of the independently generated data sets, meta-analysis of microarrays remains a difficult task.
Microarray techniques are based on the hybridization of cDNA samples to immobilized probes on microarray slides, whereas the SAGE method generates a library of expressed genes by taking a raw count of sequence tags, each representing a transcript in the RNA population.
Microarray techniques were according to Agilent's One-Color Microarray-Based Gene Expression Analysis (Quick Amp Labeling) manual Version 5.7 (Agilent; www.agilent.com).
AZ established the microarray techniques.
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