Sentence examples for model with false from inspiring English sources

The differential gene expression analysis was performed using Illumina custom error model with false discovery rate correction implemented in GenomeStudio [ 80].

By refitting the model with false dates for smoke-free legislation, we found that none of the false dates led to a significant impact in the population as a whole or in men of any age.

Proteome datasets were analyzed using the Poisson regression model combined with False Discovery Rate (FDR) of 1%.

The perfect predictive model, with no false-positive or false-negative results, would have an Az of 1 and, on the contrary, a model with an Az almost equal to 0.5 would not discriminate between ICU survivors and non-survivors.

Specifically, for nodule detection, MTANNs generated 2.7 false positives per patient at 100% sensitivity, which was significantly (p<0.05) lower than the best performing CNN model with 22.7 false positives per patient at the same level of sensitivity.

In the end though they were able to train a model with a false positive rate – the number of people wrongly classed as terrorists - of just 0.008%.

We show also the connections of our model with the false discovery rate approach.

Expression changes in transgenics were measured relative to XX controls, and the significance determined using the Illumina custom error model with Benjamini/Hochberg false discovery rate correction.

Table 3 shows that repeats flanking the first and second introns in Holosticha and the first introns in Uroleptus and Urostyla are significantly rare in the eukaryotic splicing constraint null model with a false discovery rate of 10%.

When comparing infected animals, only 4 probes from 3 genes (D site albumin promoter binding protein, RIKEN cDNA G530011O06 gene, testis expressed gene 11) were different between WT and Nlrc4−/− mice (Table  1, using the formula [ WTstim – WTunstim) - (Nlrc4−/−stim- Nlrc4−/−unstim)] with a generalized linear model with a false discovery rate of <5%) (Table  1).

If MMSEQ's posterior FPKM variances are taken to represent the expression-level uncertainty (as we did in our model) this results with false negatives in cases where a silenced or nearly silenced allele is in the left mode but due to this artificially high uncertainty the parental bias does not come out as significant.