Multi-study inference of regulatory networks for more accurate models of gene regulation
Fig 5
Recovery of prior interactions depends on prior quality and is robust to increasing prior weights.
Distribution of number of regulators per target in the B. subtilis prior (A), for the S. cerevisiae gold-standard (B), and for the S. cerevisiae chromatin accessibility-derived priors (C). (D) Distributions of MTL inferred confidence scores for interactions in the prior for each dataset. Different colors show prior weights used, and represent an amount by which interactions in the prior are favored by model selection when compared to interactions without prior information. (E) Distributions of MTL inferred confidence scores for true (yellow) and false (gray) interactions in the prior for each dataset. (F) Counts of MTL inferred interactions with non-zero confidence scores for true (yellow) and false (gray) interactions in the prior for each dataset.