Sentence examples for dataset was evaluated for from inspiring English sources

To evaluate the validity of the findings from the 35-patient dataset, a second dataset was evaluated for associations between PGx and PK.

In an additional experiment, the overlap level of extracted biclusters in yeast stress dataset was evaluated for BICLIC, BCCA, CPB, and QUBIC.

The cycling dataset was evaluated for overrepresentation of GO Slim categories to determine whether the maize circadian clock preferentially regulated specific plant processes.

The resulting consensus tree from Bayesian analyses for each dataset was evaluated for branch lengths using TREE-PUZZLE 5.0 by maximum likelihood algorithm with a gamma-distribution, the GTR model for nucleotide substitution and the JTT model for amino acid substitution[ 72].

To our knowledge, the number (32) of real experimental datasets we analyzed is much larger than those analyzed by previous methodological studies: Two experimental datasets were evaluated for the ibmT [ 20] method and one was for the shrinkT [ 23] method.

Meta-analysis of tumors from breast cancer patients obtained from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets were evaluated for levels of BST-2 expression and for tumor aggressiveness.

For selection of parameter λ, the threshold for being classified as abnormal tissue, we divided our dataset into two sets of 15 patients as training and test datasets, and was evaluated for a range of values λ  ∈ {0.1, 0.2, 0.3, 0.4, 0.5} to select the optimal λ value.

Furthermore, the potential influence of dataset diversity on PADIF scoring success was evaluated: For each protein dataset, the pairwise ECFP4 [35] Tanimoto similarities between all ligands were calculated [36] and binned (Additional file 1: S4).

For the common PCR case, where PCA was applied on the genotypic data from the reference dataset, the pattern of accuracies was evaluated for an increasing number of PC that were included in the model based on decreasing eigenvalues.

Heterogeneity of residual standard deviations (SD) and coefficients of variation (CV) among effect classes was evaluated for each dataset in Table  1.

The parameters of the model were estimated by cross-validation, and the ability of the prognostic signature to predict OS or DFS was evaluated for the respective datasets.