Multi-study inference of regulatory networks for more accurate models of gene regulation
Fig 4
Multitask learning performance boost outweights benefits of other data integration methods.
Assessment of accuracy of network models learned using three different data integration strategies, data merging and batch correction (STL-BC), ensemble method combining models learned independently (STL-C), and ensemble method combining models learned jointly (MTL-C). (A) Precision-recall curves for B. subtilis, again using a leave-out set of interactions. Barplot show mean area under precision-recall curve (AUPR) for each method. Error bars show the standard deviation across 10 splits of the gold-standard into prior and evaluation set. (B) Precision-recall curves for S. cerevisiae, with the difference that the prior is from an independent source (no splits or replicates).