Fig. 1: Workflow of the subset-selection algorithm.
From: Uncovering cancer gene regulation by accurate regulatory network inference from uninformative data
a The subset-selection algorithm, where each gene is removed together with its knockdown experiments, and SNR of the remaining dataset is measured. The gene is then put back and the procedure is repeated for all genes in the dataset. b The inner part of the algorithm showing the changes in SNR after each removal and the detection of the gene whose removal increases SNR the most and therefore will be permanently removed. c The simulation step applied for the calculation of the expected accuracy of the GRN inference, where Atrue refers to the true GRN that can either be fully synthetic or estimated from the real data, Ysim denotes the generated expression matrix from Atrue, Ainferred is the inferred GRN, while the accuracy was evaluated in terms of the area under the ROC and precision-recall curves.
