Sentence examples for dataset analysis approach from inspiring English sources

For the first time, the dataset analysis approach was used in 2002 [ 9], when significant fractions of cancer-associated and cell-signaling proteins were found to contain predicted IDRs of 30 residues or longer (see Figure 4).

While we find that that individual gene analysis results are highly variable across similar datasets, using a gene pathways analysis approach shows promising evidence that genetic pathways can further stratify survival across datasets.

In this study we have assembled data from ER+ tumours within five published large-scale microarray gene expression datasets and developed a computational analysis approach to score the contributions of genomic regions with altered gene expression to proliferation and hence grade.

We compared the leaf RNA sequencing dataset with the present leaf dataset to demonstrate and confirm that our microarray analysis approach towards transcriptome profiling was appropriate.

Power analyses suggest sample sizes of 3 25 depending on sequencing depth and budget [ 37] while others have examined 2, 4, and 5 replicates using synthetic datasets and various analysis approaches [ 20].

Thus, a convergent analysis approach involving multi-dimensional datasets combined with network or pathway analysis might serve as a comprehensive approach for disease candidate gene prioritization.

There was substantial convergence of the results from these two GWA datasets using the non-template (1) "converge then cluster" GWA analysis approach.

For comparison with the classical multivariate analysis approach, a PCA was performed on the samples of the dataset.

Using a similar analysis approach to Sridhar, both the SmvsNS and the BuccalCompare datasets were compared against six gene lists in a GSEA enrichment analysis.

Using a subpathway analysis approach, we identified numerous well-known and previously unknown pathways enriched in datasets from both diseases.

A combined gene expression data analysis approach has been employed to investigate the impact of VDAC1 expression on survival, which was statistically significant in all individual datasets examined.