Sentence examples for dataset tend to from inspiring English sources

The solutions heavily based on the inland GPS dataset tend to map the slip more close to the hypocenter and have a significant reduce in slip toward the trench (e.g., Simons et al., 2011), inconsistent with our solutions.

As expected, the CNV detection using PennCNV in this heterogeneous dataset tend to be inaccurate.

Indeed, nocturnal species in our dataset tend to occupy the lower right corner of the plot of PC 2 and PC 3, even though there is considerable overlap with diurnal fish.

In the current study, we look at duplication and loss patterns across a large genetic dataset to ask if genes in our dataset tend to duplicate and be lost in tandem, showing patterns of co-duplication/loss.

Background amino acid frequencies estimated from a small dataset tend to have bias, while amino acid frequencies from large databases may not be suitable for the specific protein family under analysis.

SNPs that are dissimilar among couples in the IMSGC dataset tend to show excessive heterozygosity in the HapMap CEU samples, while markers that are similar among IMSGC couples show excessive homozygosity in the HapMap samples (chi-square p < 0.004, expected values shown in parentheses).

In contrast, peaks called from the GABP dataset tended to be wider, with median peak widths ranging from 300 to 800 bp, excepting CisGenome which was only 90 bp (Figure S10).

Overall, the positively selected K a / K s values computed from the Treated dataset tended to be slightly higher than those from the Specialty dataset.

However, the SVM model that is constructed from an imbalanced dataset tends to draw the hyperplane away from the ideal place and towards the minority side.

A PCA analysis of this dataset tends to group the biological replicates generated from the same condition and separates the samples according to the bacterial association for either the free AAs or the dipeptides datasets.

The apparent misclassification error rate, which is the number of misclassified observations in the training dataset divided by the total number of samples in the training dataset, tends to under-estimate the true misclassification error rate [ 32].