Sentence examples for datasets were identified using from inspiring English sources
Importantly, these transcription factor binding site datasets were identified using the mincing strategy and therefore allow a direct comparison with the pulverization method.
Potential outlier datasets were identified using robust Mahalanobis distance squared values associated with the peptide abundance vector (rMd-PAV) and a p-value threshold less than 0.001 as recommended by the developers of the algorithm [ 22].
Genomic binding sites in the ChIP-Seq datasets were identified using the peak calling algorithm MACS (version 1.4.0 beta) with default settings (band width = 300, model fold = 10, 30, p-value cutoff = 1.00e-05, range for calculating regional lambda = 1000 and 10000 bps) [ 62].
As obesity is often associated with a number of health problems, the presence of comorbidities in the Primary Care dataset were identified using the Charlson Index.
In the Tokyo dataset, SLNs were identified using a radioactive tracer (99mTc-phytate).
In the Seoul dataset, SLNs were identified using both blue dye and a radioactive tracer.
In the Kyoto dataset, they were identified using blue dye and a fluorescence navigation technique using indocyanine green.
For the full E14.5 liver datasets, differentially methylated regions were identified using the R package bsseq [ 30].
Periodically expressed targets that showed statistically significant differences in expression (false discovery rate q-value ≤0.05) in the normalized datasets of 36 summer samples were identified using the GeneCycle R package [ 39].
Although the context+ model was trained using multiple regression on 74 high-throughput datasets, the features used to distinguish effective sites (the three features of the original context scores) were identified using only 11 datasets, implying that additional features might be identified through analysis of the additional datasets.
All the topological parameters were computed based on the GCC [ 36].After that, the differentially expressed genes were matched to the arranged PPI datasets, and the top hits genes were identified using the characteristics of betweeness centrality and degree in PPI.
