Figure 2

Results of unregularized and L₁-regularized fitting without constraint on regulatory architecture. (A) The estimated regulatory architecture for the gap gene network. Dashed black links are false positives that are not in the gold standard model. Dashed red are missing links that are in the gold standard. (B) Statistics regarding the accuracy of regulatory architecture, as estimated by the simulated annealing (SA) approach of Jaeger et al.[7, 8], the hybrid optimization approach of Perkins et al.[33], and the functional data analysis (FDA) approach tested in this work. CF is the fraction of relationships correctly identified as –, 0 or +; PPV is positive predictive value; Sens is sensitivity; and CSF is the fraction of nonzero links in both the gold standard and the estimated architecture that have the same sign (+ or –). (C) The effects of L₁-regularization on total correct links (Corr), true positives (TP; interpreted as links shared by the gold standard and the model, regardless of sign) and true negatives (TN; interpreted as links absent in both the gold standard and the model). (D-F) The same information for the fits to the IRMA data. In panel E, TSNI refers to the best-performing approach as tested by Cantone et al.[29]. (G-J) Estimated architectures for the GeneNet Weaver networks S1, S2, D1 and D2 respectively. (K) Summary statistics for the accuracy of FDA reconstruction of the regulatory archictectures. (L) The L₁-regularized performance of the FDA approach on the sparse networks S1 (solid lines) and S2 (dashed lines).