We obtained much higher QSAR correlation coefficients (r) for flavonoid end-point antioxidant activity in all three assay systems using the FP method (0.966, 0.948, and 0.965 for datasets evaluated in the biochemical, enzymatic, and whole cell assay systems, respectively).
The 35-patient dataset evaluated in this study was small with regard to exploratory PGx, and therefore an additional dataset from 51 patients was used to evaluate the validity of the findings.
Importantly, only 33.3%% (12/36) of all microarray datasets evaluated in Haibe-Kains et al. [ 6] had all the PAM50 genes available, whereas 100%% of the datasets had all three genes of the SCMGENE assay, thus highlighting another caveat of this study.
In contrast, the satisfactory predictive value of the clinically easy to determine dataset evaluated in PreDiSc was the rationale to use this score as screening procedure in a prospective study.
In summary, in all NSCLC datasets evaluated, we observed down-regulation of IR-B mRNA expression with an associated increase in the IR-A/IR-B mRNA ratio in a subpopulation of patients.
The classifiers defined by complete training in the Fontaine dataset were evaluated in five other thyroid datasets (Table 4).
We are concerned here with external validation of a published Cox proportional hazards model developed in a single dataset and evaluated in one or more independent datasets.
This dataset is evaluated in comparison to four other databases (three protein sequence databases and one trichome-specific Trinity contig database [ 14]) with regard to their suitability for proteomic analysis.
In this study, the entire dataset was evaluated in order to characterize the learning curves of both HEC and LICK and, more specifically, to determine if pre-training HEC has an influence in the LICK learning curve.
The highest precisons for each MIPS category in each dataset evaluated are shown in bold.
