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For a set of proteins the average of all POVs over the total number of proteins N is: To evaluate the average standard deviation of our predictions, we performed a bootstrapping procedure with 100 runs over 60% of the predicted data sets.
To evaluate confidence in the predictions, we performed several qualitative assessments, such as mapping where predictions were made outside sampled covariate ranges, and comparing them with maps of sightings from a variety of sources that could not be integrated into our models.
To assess the quality of our predictions we performed a high-resolution genomic analysis of the miR expression in the underlying tumor and control cases.
For these predictions we performed GeneSV calculations twice.
Online, and using the resulting predictions, we performed comparisons of calibration, accuracy, and discrimination.
In order to evaluate the robustness of created predictions we performed GeneSV calculations twice.
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For each of the 32 predictions, we perform a one-tailed two-sample t-test for equal means against the DME controls.
After target gene prediction, we performed GO analysis on the predicted target genes of 137 differential miRNAs (P < 0.01) that changed in DP and IDL samples.
To test this prediction, we performed 108 mating experiments and found no association between mating probability and genetic or geographical distance.
To demonstrate experimentally the validity of this very general prediction, we performed transport measurements on a.c.-driven vortices trapped in a superconductor by an array of nanometre-scale asymmetric traps.
To test this prediction, we performed a series of radioactive in vitro kinase assays.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com