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Overall, frequency-based ranking seems to perform better than relative entropy-based ranking.
When comparing the frequency-based ranking to the set of genes in the published 70-gene and 231-gene signatures, there appear to be additional genes with high frequencies of occurrence that were not part of the published signatures.
Concerning the statistical ranking of the result set, the frequency-based ranking method performs better than the relative entropy-based ranking for biomarker gene enrichment of the diseases investigated in this study.
Therefore, in the experiment, we compared different strategies for reference feature selection, e.g. Chi-square, and frequency-based ranking, and different classifiers for RDE ensemble such as SVM and random forest.
Although frequency-based ranking leads to higher gene enrichment slope between the ranks 300 and 1500, we observe a stronger enrichment at low ranking positions using relative entropy-based ranking.
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({K_{f}}) is the frequency-based rank.
From the sub-trajectory (mathcal{T}) we compute the frequency-based ranks (K_{f}) of all locations visited so far.
(a) The recency-based rank of D1 has exponents (alpha_{K_{s}} approx 1.644) and exponential cut-off (kappa_{K_{s}}approx40.94), whereas the frequency-based rank distribution has a better fit for (alpha_{K_{f}}approx1.56) with (kappa_{K_{f}} approx23.6).
The consistency analysis reports that (1) the frequency-based method is more consistent than the societal risk-based method, and (2) the empirical Bayesian method is more consistent than the simple ranking method.
A frequency-based gene selection method to identify robust biomarkers for radiation dose prediction.
Frequency-based test statistics clearly show significant departures from neutrality for both subgenomes (Fig. 1c).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com