  In this work, we describe a computational framework for the genome-wide
identification and characterization of mixed
transcriptional/post-transcriptional regulatory circuits in humans. We
concentrated in particular on feed-forward loops (FFL), in which a master
transcription factor regulates a microRNA, and together with it, a set of joint
target protein coding genes. The circuits were assembled with a two step
procedure. We first constructed separately the transcriptional and
post-transcriptional components of the human regulatory network by looking for
conserved over-represented motifs in human and mouse promoters, and 3'-UTRs.
Then, we combined the two subnetworks looking for mixed feed-forward regulatory
interactions, finding a total of 638 putative (merged) FFLs. In order to
investigate their biological relevance, we filtered these circuits using three
selection criteria: (I) GeneOntology enrichment among the joint targets of the
FFL, (II) independent computational evidence for the regulatory interactions of
the FFL, extracted from external databases, and (III) relevance of the FFL in
cancer. Most of the selected FFLs seem to be involved in various aspects of
organism development and differentiation. We finally discuss a few of the most
interesting cases in detail.
