We found that the sequence‐based features distinctive to the four helix‐helix contact classes in the Walters and DeGrado dataset are likely to be less well defined in the PDBTM‐derived dataset.
Signature genes of the 5 subclasses (Basal-like, HER2, Luminal A, Luminal B, and Normal breast-like) were defined in the largest dataset (N = 295) [16] based on prediction made with "Sorlie2003 single sample predictor (SSP)" [17], and evaluated in 3 datasets of independent patient series generated on various microarray platforms [17] [19] (Table 1).
All the diagnostics were defined in the patient dataset using the ICD-10 classification.
Baseline characteristics were collected, using these systems, as defined in the minimal dataset of NICE, which includes general characteristics, such as age, sex, acute and chronic diagnoses, number of admissions, mortality and standardized mortality ratio, Variable Life-Adjusted Display curve, start time and end time of mechanical ventilation, and discharge data from the ICU and hospital.
Ideally, the groups selected should be defined in the applicable datasets relating to local production, as well as imports and exports (domestic and foreign).
We constructed a series of binary variables to isolate different characteristics of democracy as defined in the Democracy-Dictatorship dataset developed by [26].
For each of the genes in the macrophage cluster as defined in the full atlas dataset, we calculated the ratio of their highest expression in macrophages to their highest expression across GI tract samples.
The three compositionally different regions were defined in the complete mouse promoter sequence dataset.
Briefly, a global classifier was learned in which the class to be predicted was gene pair functional relationships (as defined in the gold standard) and each dataset formed one node in the network.
Two datasets were defined in the analysis, namely, ingroup and outgroup, where the outgroup dataset included only M. sylvanus.
