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Mean area-under precision vs. recall curves for DREAM3 five -gene networks.

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posted on 2013-02-21, 02:08 authored by Aviv Madar, Alex Greenfield, Eric Vanden-Eijnden, Richard Bonneau

We evaluated the performance of Inferelator 1.0 and three different versions of CLR—namely: original-CLR (CLR), dynamic-CLR, and mixed-CLR—with or without Inferelator 1.0, at three levels of knock-out filtration, . To make DREAM3 predictions we used mixed-CLR with Inferelator 1.0 (with filtration cutoff ), resulting in area-under precision vs. recall curve of (p-value, ), and area-under receiver operating characteristic curve of (p-value, ). We show that the pipeline we used to make DREAM3 predictions produced optimal performance, compared to other tested CLR/Inferelator 1.0 combinations. Error bars for methods involving Inferelator 1.0 (variability due to cross validation) are approximately within of Precision vs. Recall area-under-curve values and are thus not shown.