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Li and Wong modelled probe level data to generate model based expression index (MBEI) and implemented it in the dChip software [ 2].
During the calculation of model based expression signal values, array and probe outliers were interrogated and image spikes were treated as signal outliers.
Data pre-processing was carried out with dChip Invariant Set Normalization and PM-only Model Based Expression summarization.
The most popular methods for calculating expression indices include Affymetrix Microarray Suite 5 (MAS5) [ 1], model based expression index (MBEI) [ 2] and robust multi-chip average (RMA) [ 3].
During the calculation of model based expression signal values, array and probe outliers are interrogated and image spikes are treated as signal outliers.
During the calculation of model based expression signal values, array and probe outliers are interrogated and images spike are treated as signal outliers.
The data was then loaded into the Gene Traffic Microarray Analysis program where it was normalized using the invariant set command, using the Clark 100 uM Fe as the control group, and a model based expression index (MBEI) [ 44] analysis was performed on perfect match probes only.
DNA-Chip Analyzer (dChip) (http://www.hsph.harvard.edu/cli/complab/dchip/) program was used to obtain model based gene expression value (measures the fluorescence intensity of that gene), then the class neighbors analysis standardizes the expression values for each gene by linearly adjusting their values across all samples to a mean of zero with a standard deviation of one.
A diagnostic model based on expression levels of ten miRNAs is constructed in the discovery set.
We have developed a model based on expression of the mDUX ORF during Xenopus development.
We have used gene expression data to build two models: a knowledge-driven model based on gene expression changes following gene perturbation experiments, and a data-driven mathematical model derived from time-course gene expression data recovered from wild-type animals.
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