Sentence examples for deviating signal from inspiring English sources

Exact(1)

The deviating signal for rs7185735 may be due to the inference of the genotype by imputation instead of by direct genotyping.

Similar(59)

Combined limma testing (p-score cut-off >0.001) and segmentation resulted in 184, 283, 6319 and 5974 probes with significantly deviating signals from QM6a in QM9123, QM9414, NG14 and Rut-C30, respectively.

Some of the genes in the region also seem to have been affected by selective forces within this clade, as inferred from deviating phylogenetic signals and elevated rates of non-synonymous substitutions.

Some of the genes in the galliform MHC-B region also seem to have been affected by selective forces, as inferred from deviating phylogenetic signals and elevated rates of non-synonymous nucleotide substitutions.

Median values were used to minimize the effect of occasional "non-uniform spots" that may have signal values deviate from average signal values but have p-values<0.01.

Increasing availability of genomic data for key taxa will permit us to specifically test these scenarios and examine alternative explanations for phylogenetic signal deviating from vertical inheritance.

Such as, in communication channels, discrete signals generated by a specific sequence from a source could be corrupted by Gaussian noise in the transmission process; so, the received signals could deviate from the signal sequence [10].

In the present study, the longer temporal integration window with higher spectral resolution in the right hemisphere appears to have dominantly contributed to detecting spectrally deviated sound signals and resulted in relatively larger MMNm_SD amplitudes in the right hemisphere.

In contrast, the shorter temporal integration window with high temporal resolution in the left hemisphere appears to have dominantly processed temporally deviated sound signals and resulted in relatively larger MMNm_TD amplitudes in the left hemisphere.

To estimate whether the biological signal deviated from the random model, we counted how many times a larger or lower signal, depending on the under- or overrepresentation of evolutionary events, was found in the random set.

It applies a range of statistical tests (linear-regression analysis is one of the more familiar) to the data stream, and thus works out when the incoming signals are deviating significantly from normal behaviour.

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