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Categorical variables were summarized by computing the absolute value and the frequency (as percentage).
Continuous variables were summarized by computing average values and standard deviation (SD), while categorical variables by computing the absolute value and the frequency (as percentage).
First, two distributions were formed by computing the absolute value of the Pearson correlation coefficient between the expression data of any two genes in the refined and original dataset, respectively.
Only the sequences with at least 80% of the maximum possible binding score on either of the alleles were further studied by computing the absolute difference of the binding scores between the alleles.
The DR-FFL algorithm described in [ 30] used the following strategies for the three steps: In a preprocessing step, a confidence weight is assigned to each possible edge i → j of the network by computing the absolute value of the standard z-score z ij.
Alternatively, in the unsupervised analysis mode, three feature rankings are obtained from the pathway expression variance matrix (rows = pathways, columns = samples) by computing the absolute variances across the columns/samples, the magnitude of the loadings in a sparse principal component analysis (Zou and Hastie, 2008) and a recently proposed entropy score (Varshavsky et al., 2006).
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Daily temperature variability was determined by computing the mean absolute second derivative of the temperature signal.
Some additional variables were analyzed: the maximum daily CRP, temperature and WCC variations (calculated by computing the greatest absolute difference from the previous day's level) and the ΔCRP (calculated by computing day 0 concentrations minus the lowest CRP value).
A one-to-one comparison of all 100 possible combinations of deformation fields obtained in the load steps performed in air and in water was performed by computing the mean absolute difference of the displacement magnitude and of the angle between the displacement vectors over 3000 sample points on the specimen surface.
To compute effectively the absolute semi-deviations of single fuzzy variable as well as its functions, this paper discusses the methods of computing the absolute semi-deviation by classical Lebesgue Stieltjes (L S) integral.
The comparison is made by computing the sum of absolute difference (SAD).
More suggestions(15)
by computing the mutual
by computing the explicit
by dividing the absolute
by computing the algebraic
by computing the isotypic
by computing the Euclidean
by computing the ionic
by computing the conditional
by computing the finite
by computing the linear
by computing the th
by computing the standard
by computing the mean
by computing the elastic
by computing the levodopa-equivalent
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