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In addition to these six engines aimed at binary classification, the prediction of the label of a therapy (success/failure), we train three engines with a target of predicting the drop in VL, i.e. regression (the minimal feature set is less adequate for this target of predicting change of VL as it requires not employing baseline VL).
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This result illustrates the well-documented difficulties of predicting targets for miRNA [43].
Bioinformatic algorithms remain the principal means of predicting targets of specific miRNAs.
For target verification using Western blot, the NEFM and SLC25A20 antibody detected a target of the predicted molecular mass.
(7, 33) In addition, various miRNA target prediction programs, which use different algorithms of targeting, produce different lists of predicted targets.
These antibody targets comprise about 16% of predicted targets in each cancer type.
The comparative analysis helps select new plausible target sites from a pool of predicted targets to be validated experimentally.
The number of predicted target genes for each target family in Arabidopsis (A.t).
From this a weighted score was calculated based on the number of predicted target site per 3′UTR, the distance between target sites and the type of predicted hybridisation.
Target enrichment: module is enriched in known targets of the predicted regulator, module is most enriched for predicted regulator.
We also used the highly conserved set of predicted targets of microRNA targeting (miRcode 11 June 2012 release) (58).
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