I am trying to find over-expressed motifs in a bipartite transcription factor gene network.My genes are not very well characterized, so finding functional motifs has been a challenge. I used the motif-discovery app on Cytoscape and calculated the total number of 3 node motifs on the network. In my network, where transcription factors regulate genes, the only kind of three node motif that is possible is a simple input module.
This is an example of a simple input module where a transcription factor regulates multiple genes
I further created random networks to my real world network and statistically (Student's t-test) proved that there are more number of single input modules in the real rather than the random network. However, I am just not feeling satisfied with just this one explanation because I would have like to draw some biological inference from this. I was thinking of also analysis the 4 node and 5 node motifs in the network, find the number of times any of my hub nodes occupy a single node of these motifs and maybe use that and prove the importance of my hub nodes (though hub nodes are worthy of more exploration just by virtue of their high degree). Has somebody done something like this previously. It is a given that hub nodes would be part of the maximum number of motifs just by virtue of their high degree and connection to multiple genes. So would this prove to be redundant?
Thank you in advance for any help that could be provided.