Sentence examples for in normal dataset from inspiring English sources

Take an example gene SRF in normal dataset to be treated as a transcription regulator gene and 494 genes are first found to be dependent with SRF using statistical test method.

Take gene SRF in normal dataset as a simple example to show the CI test between SRF and its transcription factor dependent genes in Table 7. Row "Dg of SRF" shows 7 transcription factor dependent genes of SRF.

Genes that were likely to be expressed in normal breast tissue were selected from these gene sets by selecting genes with variance >1 in the normal tissue data; 7.3% of genes in the normal dataset have variance >1, and enrichment for high variance genes in the various gene sets was measured by a χ2 goodness of fit test.

We also challenged the prediction accuracy of models developed from the tumour data by performing the corresponding comparison in the normal dataset.

By contrast, selection for mRNAs with at least one co-expressed lncRNA (i.e., highly correlated pairs, r>0.7; Figure  1B) showed the presence, in the normal dataset, of a clear bimodal distribution.

Furthermore, there is lack of evident vertical stripes, despite the presence of sporadic light spots.In the normal dataset, the unimodal and zero-centered distribution of Pearson correlation coefficients between all miRNAs and all mRNAs, when limiting miRNAs to that subset which is responsible for the light vertical stripes in the sensitivity correlation heat-map, approaches to a bimodal curve.

In addition, there are 36 links that contain 10 transcription regulator genes which contain inhibitive expressions in the cancer and activate expressions in the normal datasets that are shown in Figure 13.

HCA of MassARRAY methylation data in the UNC tumor/matched normal dataset, followed by validation of methylation patterns in TCGA tumors and matched normal tissues revealed the six methylation patterns described herein.

We take the interactions with the activate expressions in the cancer and the inhibitive expressions in the normal datasets and vice versa.

Reliable estimates of degrees of freedom were obtained in all simulated heavy-tailed and normal datasets.

As much as 70%% of malicious SWF files in the SWF-Normal dataset were collected before the first evaluation period, while less than 10%% of benign SWF files occur before the fifth evaluation period.