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These descriptors should then be evaluated in an unbiased manner and preferably using an external dataset [10].
In addition to the internal evaluation using link perturbation approach, we evaluate the performance of our method using an external dataset, namely ChEMBL version 15 database.
In this work, we apply a random walk-based link prediction algorithm based on Chen et al. [3] to a more extensive drug target network and evaluated its performance using an external dataset.
Finally, to demonstrate accuracy of prediction using an external dataset, we showed that sites matching predicted motifs for ZNF263 are significantly enriched in recent ZNF263 ChIP-seq data.
Finally, to demonstrate prediction accuracy using an external dataset, we tested de novo discovered motifs in promoters of predicted ZNF263 targets for enrichment in ZNF263-bound regions according to ChIP-seq [30].
Independent validation of signatures (for OS) using an external dataset from TCGA further strengthened the study findings.
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We apply the RWR algorithm to a drug target network and use an external dataset extracted from ChEMBL 15 (544 drugs and 467 proteins) at bioactivity cutoff points of 10 and 1 μM to quantitatively evaluate the performance and robustness of the approach.
Evaluation using an external validation dataset and bootstrap analysis revealed high AUC values of 0.772 and 0.768, respectively.
This shows that our implementation of TLR3 is comparable to established standards when using an external, focused dataset.
We also further confirmed the assumption of normality using an external HTS dataset of two duplicate 384-well plates containing dimethyl sulfoxide (DMSO) negative controls and no treatment (W = 0.9978, P value = 0.9007 and W = 0.9961, P value = 0.4602).
The mapping of polynomial parameters was validated using an external SOC profile dataset and showed a poor prediction of the surface content but a good prediction of the depth distribution once the surface SOC content is known (RMSE = 0.15 0.25%C).
More suggestions(15)
using an external router
using an intercontinental dataset
using an Italian dataset
using an external programming
using an external data
using an underpowered dataset
using an external surface
using an external rf
using an unknown dataset
using an external stimulus
using an informative dataset
using an exhaustive dataset
using an external light
using an external software
using an external position
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