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We then test how many "misplaced" leaves our method is able to detect.
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From left: our method; PC; LFR; FDDE; LSS; MI.
From left: our method; PC; LFR; FDDE; LSS; MI. Figure 13 Correlation surfaces for the images of Figure 1 b.
Figure 10 Comparison between the cropping sphere technique (left) and our method (right).
From left: Optical image; Our method; PC; LFR; FDDE; LSS; MI. Figure 10 Matching results of the proposed method.
It also shows that our method leaves little room for improvement particularly for small selectivity values.
Here, we simply explain the basic idea of our method, leaving its analysis to the Appendix (Supplementary Information).
Such a symmetry is necessary in our method because ICA algorithms leave permutation ambiguities.
So far our method for disease comparison left molecular interactions unspecified and addressed only the overlap of causal gene sets.
We acknowledge that with no precedent for this type of analysis, our methods leave room for improvement.
We tested our method by the leave-one-out cross validation scheme, a novel independent dataset, and tissue specific miRNAs.
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CEO of Professional Science Editing for Scientists @ prosciediting.com