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To achieve high confidence drug prediction, multiple microarray experimental results were merged by performing meta-analysis.
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Hu et al. have proposed quality-adjusted effect size models that were used to integrate multiple gene-expression microarray data given heterogeneous microarray experimental standards [ 107].
Presently, consensus has not been reached regarding the appropriate method for combining the results of multiple microarray studies, while taking into account the differences in experimental methodology, to obtain improved understanding of the overall pattern of differentially expressed genes.
A scalable method for integration and functional analysis of multiple microarray datasets.
Here, we proposed the integrated information management architecture for microarray experimental data.
Because there are multiple microarray elements matched for some genes, the heatmap and line plot are displayed according to microarray element IDs.
A detailed description of the microarray experimental design is shown in Supplementary Table S1, sheet "MA design".
Highly variable microarray experimental conditions and the use of different microarray platforms cause poor reproducibility of microarray measurements within and between laboratories [7] [11].
The microarray experimental design was made according to the MIAME recommendations [8].
The classes one-color microarray experimental process and two-color microarray experimental process also specialize DNA microarray experimental process.
Analysis of microarray experimental data available for SCN (H.
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