SRF regulatory circuits. Five known SRF co-factors are selected to study their modular regulatory roles. Based on shared target genes and significant interaction effects γ from the model, SRF regulatory circuits are identified as having significant effects on expression of target genes. SRF, serum response factor.

Enrichment of MIPS functional annotations. The hypergeometric distribution was used to calculate P values to determine the enrichment of MIPS functional categories, and P values smaller than 0.001 were considered to indicate significant over-represention. For each of the 39 TFs analyzed, (a) the number of significantly over-represented MIPS categories in the functional targets (B+/C+ [red] and B-/C+ [yellow] clusters) and nonfunctional targets (B+/C- cluster [blue]) are summarized. (b) The percentage of genes categorized into significantly over-represented MIPS categories in B+/C+ (red) and B-/C+(yellow) clusters and B+/C- set (blue). TF, transcription factor.

Prediction performance with various weights on two priors. To examine the effect of our prior information on prediction, we used a restricted COGRIM model that assigned fixed weights w (ranging from 0 to 1) to the ChIP binding data. The x-axis represents the assigned weights and the y-axis represents the number of predicted true C/EBP-β targets in 16 validated ones (black square spots). The sampling procedure automatically assigned an appropriate weight 0.92 (variance 0.006) to ChIP-chip binding data (red diamond spot). C-EBP, CCAAT/enhancer-binding protein; ChIP, chromatin immunoprecipitation.

Significant TF pair interactions. Eighty-four TF pairs were identified to have significant synergistic effects on expression of target genes. Nodes represent TFs and edges indicate that two connected TFs form a module to regulate a set of genes. The TF pair is determined to be significant if they share at least four functional target genes and if the posterior interval for the interaction effect term g_jk is significantly different from zero (details given in Additional data file 1 [Supplementary methods]). The target genes of each regulator are not shown. Regulators without significant interaction with other TFs are not shown. This network is illustrated with Cytoscape [33]. TF, transcription factor.

COGRIM improves gene classification in HAP4 case. For each of HAP4 gene clusters, genes are ordered by the ChIP binding P value obtained from Lee and coworkers [3]. (a) The expression profile of HAP4, a well characterized factor that is involved in respiration, across approximately 500 experiments. (b) The B+/C- gene cluster (33 genes). With ChIP binding data alone, these genes are considered HAP4 targets but they do not share similar expression patterns (averaged centered pearson correlation is only 0.06) and none of them was assigned to the MIPS respiration category. COGRIM does not consider these genes as HAP4 functional targets. (c) The B+/C+ gene cluster (34 genes). This gene cluster shows high expression correlation (the averaged centered pearson correlation is 0.56), and 23 out of 34 genes were assigned to the MIPS respiration category. (d) The B-/C+ gene set (17 genes). These 17 genes were not identified as HAP4 targets by using binding data alone (with P value threshold 0.001) but were predicted by COGRIM to be functional targets. They exhibit coherent expression (the averaged centered pearson correlation is 0.60) and nine of them (ybl030c, ydl004w, yfr033c, yjl166w, yjr048w, ykl141w, ykl148c, yml120c, and ynl055c) are involved in respiration. ChIP, chromatin immunoprecipitation.