Sentence examples for datasets were evaluated using from inspiring English sources

Performances for all algorithms with different datasets were evaluated using two worker nodes.

Association between gene expression of the GIPC1 KD signature and each clinical variable in the breast and ovarian cancer datasets were evaluated using globaltest [27].

Results of the docking for nine DUD datasets were evaluated using AuPosSOM clustering followed by scoring with the scoring function developed in this study.

Datasets were evaluated using the community annotation including GO (Gene Ontology) classifications from the T. reesei genome database v2.0 provided by JGI (http://genome.jgi-psf.org/Trire2/Trire2.home.html) with revised annotations from [ 14].

The validity and consistency of the experimental dataset are evaluated using a simulation software package, modular modeling system (MMS).

The GWAS dataset was evaluated using the ICSNPathway, which showed seven candidate SNPs, five genes, and seven pathways that may contribute to the susceptibility of patients to ESCC.

Concordance of the two genes (ND2 and ND4) used to construct the dataset was evaluated using the partition-homogeneity test with the software PAUP* [41].

The performance of the lncRNA profiles in the independent validation dataset was evaluated using the LOOCV procedure described above.

A recent study [ 2] reported that the use of the probability of positive log ratio (PPLR) method [ 19] combined with mmgMOS was the best when another spike-in dataset was evaluated using AUC.

In order to conduct a statistical evaluation, the ORS r(M t) score of the true motif of each dataset is evaluated using two large sets of (i) conserved (M c) and (ii) random models (M r).

Although the three algorithms from best to worst were DFW, RMA, and MAS when artificial spike-in datasets (Datasets 1 and 2) were evaluated using the AUC metric with the eight methods (Table 1), their performance might not be generalizable in practice [ 79].