Sentence examples for to random datasets from inspiring English sources

While Negatome is complementary to random datasets for training algorithms that predict direct protein interactions, it is not a suitable candidate for testing predictions of co-complex relationships or pathway co-membership.

The performance of the algorithm was tested by the application of the algorithm to artificial random datasets with different expression profile vector dimensions.

To correct for this network bias, we also calculate a network-bias-corrected P-value that measures significance of the overlap between the dataset and regulated genes by comparing to overlaps of random datasets with distributions of in-degrees similar to the actual dataset, and therefore preserving network topology.

Specifically, we randomly assigned the presence of Wolbachia Group 2 to the 47 individual flies used in our dataset to generate 100 random datasets.

The genomic co-ordinates of microarray tiles were randomized within any single dataset 100 times to generate 100 random datasets across the ENCODE regions (or whole genome where appropriate).

We then applied SIOMICS to the two random datasets.

For this test, we randomly assigned Wolbachia infection status to the individuals screened [ 26] for which we had host haplotype (N = 366) to generate 100 random datasets.

We (i) shuffled the labels of the individuals in the autism dataset 100 times to obtain 100 random datasets, (ii) ran MIRA and RA on these datasets, as well as on the original data, and (iii) sorted and plotted the scores in descending order for all 101 instances.

To assess significance of positional biases, PEAKS uses random datasets to estimate a P value for each binding factor.

Finally, we used two batteries of random datasets to assess whether the model is indeed able to reject flux distribution that do not correspond to actual states of P. pastoris cultures.

Instead of comparing the scree plots of newly generated datasets with that of the original one, we used the distribution of percentages explained by the first two components in random datasets to assess the significance of components extracted in the original dataset.