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The relaxed cutoff required expression values in at least one sample of the set to pass the detection cutoff.
For microarrays, the stringent cutoff required expression values of a given gene to pass the detection cutoff (see above) in all samples of the dataset: five individuals or two pooled samples.
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Furthermore, biological interpretation requires expression values for genes, which are often represented by several spots or probe sets on a microarray.
The restriction to interval (0,1) was necessary as the model used here (described in Section Evaluation criteria) requires positive expression values for all genes, and facilitates computation by restricting its output to the same interval.
A new predictor of survival with similar predictive power as the proliferation signature of 20 genes [ 6] was developed requiring gene expression values of only seven genes.
The conversion of probe intensities to expression values requires two statistical procedures: normalization and summarization.
Reliable estimation of mRNA degradation rates requires accurate scaling of expression values to ensure that the ratio of hybridization signal intensities is equal to the ratio of mRNA abundance uniformly across the entire range of values.
Expression data require special treatment as the expression values are usually not specified in genomic coordinates, but rather are associated with gene names or chip probe identifiers.
However, to detect temporal patterns in gene expression, it is necessary to consider all time points, which requires simultaneous visualization of multiple expression values.
As the smoothing approach presented requires at least 25 gene expression values to make a prediction, theoretically, the resolution of a REB could average ~2.5 Mb across the genome and range between ~1 to 4 Mb.
Rank product method does not require the recalculation of the normalized expression values.
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