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A robust small-molecule microarray platform for screening cell lysates.
In this study, we test the suitability of a high-density oligonucleotide microarray platform for direct, quantitative detection of GMOs found in the Turkish feed market.
We report here a new in situ synthesized oligonucleotide-based microarray platform for Mycobacterium tuberculosis that has been updated for the latest genome information and incorporates hitherto unannotated genes with described biological functions.
The aim of this report is to explicate the design, development and evaluation of a microarray platform for use as a screening tool that combines ease of use and rapid identification of a number of rodent-borne pathogens of zoonotic importance.
Unlike the previous experiment, the microarray platform for this dataset is the RAE230A, which consisted of 15923 probesets.
The Affymetrix GeneChip is a commonly used microarray platform for genome-wide expression studies.
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External RNA controls (ERCs), which can be either added to the total RNA level (tERCs) or introduced right before hybridization (cERCs), are designed and recommended by commercial microarray platforms for assessment of performance of a microarray experiment.
Within GEO, the Affymetrix HG-U133A and HG-U133 Plus 2.0 are the two most commonly used microarray platforms for human samples; the HG-U133 Plus 2.0 platform contains 54 220 probes and the HG-U133A array contains a proper subset (21 722 probes).
There is great current interest in developing microarray platforms for measuring mRNA abundance at both gene level and exon level.
In the present study, the proposed method for determining gene signature is straightforward and independent of different microarray platforms (for example various uncommercial cDNA chips and Affymetrix chips).
Generally, consistent model performance exists across different microarray platforms for multiple-class prediction, both for the complete set of samples and for those with different RHI scores, regardless of the ACs, probe-mapping methods, and classification algorithms.
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