Sentence examples for false modified from inspiring English sources

Exact(1)

This threshold was chosen so that a reasonable number of points (1206) were available to estimate the likelihood function, while also filtering out false modified peptides.

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Laboratory challenges included a false negative modified Hodge test and reversion of carbapenem resistance in the E. coli strain.

The authors used a modified false discovery rate approach (false discovery rate-beta uniform mixture, or FDR-BUM) [ 67] to declare significance at the genome-wide level.

Satellite band combination for mining operations (yellow-NIR1-red edge), modified false color Infrared (NIR1-green-blue), and soils and constructions (red-blue-yellow) have also been of immense utility.

This method, called modified false discovery rate (modFDR), is included in Pyicos (Supplementary Material).

The input data are noisy and may contain false positives and modified peptides that do not fit into proper PTM groups.

Multiple testing of 78 SNPs in RP for both men and women followed by 14 LR models resulted in a modified false discovery rate (FDR) significance level of 0.009.

Precision, normally given by true positive over sum of true positive and false positive, was modified to report the percentage of co-OSN regions out of putative enhancers that were originally Enh or PrL.

A primary data set was generated using cells of lymphoid origin from normal children; the expression of 688 genes (ANOVA false discovery rate modified p-value, q < 0.1) was associated with age, and subsets of these genes formed clusters that correlated with the phases of growth – infancy, childhood, puberty and final height.

The true positive rate (TPR), true negative rate (TNR), and modified false positive rate (mFPR) of the predicted top 1 network in terms of AIC (BIC) score, are reported, where TPR (also known as sensitivity) is the percentage of correctly predicted links out of the total number of existing interactions (links) in a simulated network.

When using a protein reference database containing an equal number of real and decoy proteins, a random (false) peptide prediction (modified or unmodified) will have an equal likelihood of choosing a peptide from either a real protein or a decoy protein.

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