Accepted_test

For the model of transcription factor (TF) binding sites motif recognition, the recognition accuracy is calculated as the partial area under ROC (Receiver Operating Characteristic) curve (pAUC). Generalizing the ROC curves and pAUC values of the two separate models to a single joint model can reveal whether the joint performance of two motifs competes with those of both participating motifs. Testing multiple possible combinations of motifs allows to detect most strongly reinforcing each other motifs. The tested motifs can represent either structurally different types of binding sites for the same TF, or binding sites of different TFs acting as part of a single multi-protein complex. Thus, MetArea predicts motifs with synergistically related functions in gene transcription regulation. The synergy criterion for the pair of motifs 1 and 2 requires the higher pAUC1&2 value of the joint model 1&2 compared to the pAUC values of both participating motif models pAUC1 and pAUC2, Ratio = pAUC(1&2) / Max(pAUC1, pAUC2) > 1. We propose the MetArea approach to clarify the participants of multiprotein complexes regulating gene transcription. It can be used either to confirm distinct structural types of binding sites for the same TF, or to reveal the motif co-occurrence respecting to composite elements formed by the same or distinct motifs, homo- and heterotypic composite elements, correspondingly. Besides, MetArea tool can point to the false positive results of de novo motif search, since for the functional motifs the synergetic growth of the performance pAUC in the pairwise joint models is expected.