Highly diverse interactions at these loci might increase their susceptibility to erroneous interactions and eventually to transcriptional dysregulation.
Protein-protein interaction networks have been often suspected to contain erroneous interactions, to be incomplete and biased towards certain type of interactions.
This reduced the possibility of erroneous interactions due to overexpression but necessitated the use of large volumes of cells in order to produce detectable amounts of final product.
Also, this implies robustness to erroneous interactions in the prior, which can have various sources, such as non-functional TF binding reported by ChIP-Seq.
Therefore, we asked whether disease-associated regulatory loci were selected against the possibility of erroneous interactions, like those reported elsewhere (De and Michor, 2011; Lin et al., 2009) or otherwise, by restricting themselves to fewer interactions.
We test our methods on one synthetic and two bacterial datasets, and show that both MEN and BBSR infer accurate GRNs even when the structure prior used has significant amounts of error (>90% erroneous interactions).
We propose that the possibility of erroneous genomic interactions and consequently functional dysregulation is minimized by means of restricting the total number of interactions of loci that are important for normal organism development.
Unexpected, erroneous human interactions often contribute to failures in complex systems.
Therefore, potentially erroneous plant insect interactions can be corrected.
Ambiguous molecule nomenclature affects, for example, analysis of protein networks using text mining by introducing erroneous protein protein interactions.
