Exact(4)
Comparison of proteomics and transcriptomics data discriminated differentially regulated protein abundance into groups depending on correlating or noncorrelating transcripts.
A companion study [ 20] examined 136 younger women (aged 20-64 years) and reported significant correlations between Swaymeter-recorded postural sway and age, but did not reveal whether postural sway data discriminated between the young and older subgroups.
The highest observed expression for both genes occurred at 6 h p.i. and then expression of apxIIA and comEA continued to decrease until 48 h p.i. PCA of all bacterial gene expression data discriminated between samples belonging to different time groups.
* Significantly different (p < 0.05) between groups in a multivariable linear model with age and gender as cofactors Quality of care was defined based on concepts of structure, process, and outcome [ 22, 23], and the interpretation of the outcome data discriminated between intervention- and process-related items of care [ 24, 25].
Similar(56)
Altogether, these data discriminate two pro-survival functions of yeast CatD and provide first insight into the physiological regulation of programmed necrosis in yeast.
From our data, discriminating between the CD4 T-cell response against external or internal antigens in the case of vaccine preparation was not possible.
Although adequate data discriminating between drug classes are unavailable, PIs appear unlikely to be carcinogenic; indeed, animal studies report nelfinavir, among other PIs, to have anticarcinogenic properties.
A precise matching of other venom serine proteinases characterized in C. s. simus is impeded by the lack of MS/MS data discriminating between the different transcript sequences (Additional file 3: Figure S3).
Different multilayer perceptrons (MLP) and support vector machines (SVM) were trained [ 33] to learn how to classify RP and HDO conditions (in light or darkness), given the indexes extracted from the data (discriminating light and darkness conditions was not considered, as it is trivial).
This study exploits the data discriminating capability of silhouette statistics, which is eventually combined with the wavelet-based vertical energy threshold technique for the purpose of extracting damage-sensitive features and clustering signals of the same class.
Notably, the first principal component, that represents the greatest fraction of the variability in the gene expression, separates the prostate-derived cells from the skin-derived cells, while the second principal component, representing the second greatest amount of information in the expression data, discriminates between UGE/epidermis and UGM/dermis samples.
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