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The area under the curve (subtracted by a null threshold of 0.5) is indicated, as well as similarity curves corresponding to a p-value of 0.001.
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Change decision can be made by performing a null hypothesis testing with a threshold.
Statistical significance tests start by specifying a null hypothesis.
When protein reference sets are unavailable, it is standard to compute error estimates by generating a null distribution of scores, and using the ratio of the areas of null and true distributions at scores ≥ s as an estimate of the FDR at score threshold s.
False Discovery Rates (FDR [48]) values were estimated as the ratio of above-threshold segmentations in a null model to above-threshold segmentations in the true distribution.
In general, the relationship between the total mass and the extension of the area having a given probability of being covered by a deposit of a given threshold is not linear, because of the non-linearity of the operation of thresholding (thresholding produces a null hazard area when the erupted mass is insufficient for reaching the given loading).
The null distribution can be generated by simulating under a null model of no positive selection.
We calculated 5% chromosome-wide significance thresholds by simulating chromosomes under a null model with no mean- and no variance-controlling QTL effects.
Specifically, if we imagine we have a list of "real sites" of length l that are generated by the model and a null generated list of N l-mers we can ask how many null sites vs. real sites score above the threshold which we vary.
Sgca-null/ JAM-A-null transgenic mice were generated by crossing Sgca-null and JAM-A-null mice, and by selecting homozygous mice for both genes.
Groups are defined by a specific density threshold.
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