Sentence examples for dataset is normalized from inspiring English sources

The domain of each dataset is normalized to the unit square [ 0,1]2 in 2−D Euclidean space, (mathbb {E}^{2}).

The domain of each dataset is normalized to the unit square [ 0,1]2 and two of these datasets are shown in Fig. 7. Fig. 7 Two real-world spatial datasets: road networks.

Each dataset is normalized in order to bring the unit variance across the data using the following two steps: (a) Calculation of row-wise mean and standard deviation for each gene in all the data files.

The original dataset is normalized so that each sample vector has 0 for mean and 1 for standard deviation.

First, the dataset is normalized, and then based on the Euclidian formula distances between antigens, which is called affinity, are calculated.

During data fitting, each nucleotide is assigned a numerical reactivity value that represents how readily that nucleotide has been able to react with the SHAPE reagent, and the SHAPE dataset is normalized such that a value of approximately 0 0.3 is unreactive, and a value of approximately 0.7 1 or above is reactive [ 8, 13].

For the calculation of each gene's final p-value, an approach described before in [ 20] was used: as the dataset was normalized with two independent normalization methods, two different datasets having different value sets for each gene were produced.

For the 36 cancer datasets generated from Affymetrix microarray platforms, the log2 intensities in each gene expression dataset were normalized using the GC-RMA normalization method (15).

Subsequently, the generated dataset was normalized with two widely used microarray data normalization methods, as there exists no gold standard normalization method, with the scope to decrease the number of possible false positives during the statistical selection step.

Each dataset was normalized using the trimmed mean of M-values normalization method proposed by Robinson & Oshlack [ 23], to remove systematic technical effects and minimize the sequencing technical bias on the data.

For this analysis, each nCounter dataset was normalized to two cell-type-specific control genes, while microarray datasets were not normalized to control genes.